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In this paper, the radial basis function neural network based on the orthogonal least squares (OLS-RBFNN) method is proposed for the first time for the calibration of the six-port receiver, which realises six-port accurate reception in the true sense. This algorithm overcomes the problems of an ageing circuit, narrow working frequency band and nonlinearity of the six-port receiver hardware. The RBFNN is a three-layer forward network, including an input layer, a hidden layer and an output layer. The transformation function of the hidden layer is the radial basis function. A six-port receiver test platform with an operating frequency band of 2.0–8.0 GHz is built to verify the performance of the six-port receiver based on OLS-RBFNN. The test signal is a 16-QAM signal with different bandwidths and different frequency bands. The test indicator uses error vector magnitude (EVM)， which represents the error between the received signal and the ideal signal sent. At last, the EVM of all tested data is less than 1.07%, and the best EVM is 0.57%. Therefore, the calibration accuracy of the OLS-RBFNN proposed in this paper is very high. [ABSTRACT FROM AUTHOR]

Discusses the statistical properties of randomly generated boolean functions. Effect of prime implicant errors in the minimization algorithms; Relationship between the number of variables in the boolean expression on the k-subcube probability to be a prime implicant.

This paper introduces a hybrid multilevel inverter (MLI) with reduced switch count, which can generate higher output voltage level with minimum number of DC input sources. The operation of this proposed MLI is carried out with unequal DC sources to achieve the desired output voltage level. The reduced MLI output voltage is set to minimal total harmonic distortion (THD) with the help of modified JAYA (MJAYA) algorithm. A JAYA algorithm with improved steps by adopting an accelerating parameter has been proposed in this research work to obtain a faster convergence of the objective function. The MJAYA algorithm has provided the suitable switching angles for the proposed three-phase 15-level MLI and reduced the output voltage THD to 2.23%, which satisfies the standard set by IEEE-519. To prove the efficiency of this proposed modified algorithm, the comparative analysis is carried out through MATLAB program and Simulink tool using common JAYA and modified particle swarm optimisation algorithms. The performance and productivity of the proposed MLI have been investigated through simulation and experimental setups. [ABSTRACT FROM AUTHOR]

In this paper, we consider a power splitting (PS)-based simultaneous wireless information and power transfer (SWIPT) system, which is having I and Q (in-phase and quadrature) imbalance hardware impairment. The prime objective of this paper is to maximize the harvested energy for a SWIPT PS system, satisfying a minimum signal to noise ratio (SNR) requirement for information signal processing in the presence of IQ imbalance hardware impairment. The paper uses four types of bio-inspired algorithms like Particle Swarm Optimisation, Artificial Bee Colony, Firefly Algorithm and Invasive Weed Optimisation to attain the maximum harvested energy considering parameters of PS ratio, amplitude and phase imbalances in a Rayleigh fading environment. The simulation results show that under ideal power conversion efficiency and minimum hardware impairments, a maximum SNR of 16.7 dB and harvested energy of 11 dB is achieved for a transmit power of 20 dB in SWIPT systems for IWO bio-inspired algorithms in the 32 QAM modulation scheme. [ABSTRACT FROM AUTHOR]

Image skeletonisation plays an important role in applications such as object identification, object's shape description, pattern recognition, computer vision, telemedicine, and image compression. In this paper, an architecture is developed for the extraction of a skeleton for the 3-D greyscale object. The algorithm used in this paper is an extension of the 2-D greyscale skeletonisation algorithm presented in the literature. The skeleton of a 3-D greyscale object is extracted by using the boundary peeling off method. The skeletonisation algorithms are computationally intensive and difficult to achieve requirements in real-time. Field Programmable Gate Arrays (FPGAs) are selected for implementation so the real-time requirements are met. The proposed architecture is implemented on Virtex-5 FPGA and tested for an 8 × 8 x 3 greyscale object. Resource utilisation of FPGA and timing performance are investigated and are encouraging. [ABSTRACT FROM AUTHOR]

Multilevel inverters are currently the subject of extensive investigation and are used primarily for medium and high voltage distribution systems. The work presented in this paper provides a cost-effective and realistic solution to mitigate power quality (PQ) problems. A Cascaded H-Bridge multilevel inverter (CHB-MLI) has been configured as a shunt active power filter (SAPF). It is well reported that large-scale use of power electronics-based devices leads to several PQ problems such as poor power factor, unregulated dc voltage, harmonics, voltage regulation etc. In this paper, an improved immune feedback control algorithm is proposed and developed to mitigate PQ issues by predicting the weighted active component of load current and to generate reference current for the grid. Extensive MATLAB simulation and experimental work have been reported for validation on a single-phase system. A low prototype model is developed in the laboratory to study and compare the steady-state and dynamic results of the proposed controller with conventional Least Mean Square (LMS) and Immune algorithm. [ABSTRACT FROM AUTHOR]

One of the capable technologies in networking systems is the Multiple-Input Multiple-Output (MIMO) technology as it provides better system capacity and a high Bit Error Rate (BER). Still, the transmit antenna selection remains as the greatest issue. More transmit antennas are necessary to achieve maximum capacity, which leads to increased power consumption. Therefore, for solving these issues in the M-MIMO system, this paper introduces a novel Wolf Adapted Herding algorithm (WA-HA) for selecting the optimal transmit antennas using multi-objective constraints that raise the capacity and Energy Efficiency (EE). The proposed algorithm combines the concept of Elephant Herding Optimization (EHO) and Grey Wolf Optimization (GWO) algorithm and it is referred to as the Wolf Adapted Herding Algorithm (WA-HA). This WA-HA algorithm optimises the number of transmit antennas and hence decides which antenna has to be chosen. Finally, the performance of the adopted method is evaluated over other traditional methods like MV-GSA, SLnO, I-SLnO, EHO and GWO in terms of various metrics like EE and capacity. In particular, the capacity of the proposed WA-HA method for ZF under set-up 1 is 51.02%, 30.61%, 22.44%, 8.163% and 55.10% better than the existing models. Furthermore, the computational time of our model is 10.96%, 26.13%, 14.08%, 13.48% and 10.26% superior to that of the existing models, respectively. [ABSTRACT FROM AUTHOR]

In this paper, an anti-jamming scheme based on transmitted multiple pulses through random initial phases and an adaptive iterative filtering algorithm is considered for counteracting range-velocity deceptive jamming in Pulse-Doppler (PD) radar system. This anti-jamming scheme relies on the fact that the digital radio frequency memory (DRFM) repeated jammer needs more than one pulse repetition interval PRI (at least one PRI) to identify the radar transmitted pulses, and therefore uses the captured pulses of the lag PRIs to reproduce multiple false targets. As a consequence, an adaptive-iterative algorithm to estimate the range-Doppler plane of the real targets in range dimension processing and Doppler dimension processing can appropriately suppress the deceptive false targets, which employed the lagged PRIs for the radar deception. Firstly, the proposed method achieves the optimal estimation of the true targets and false targets in the range dimension. Then, with the estimation information in the range dimension, the presented method estimates the range-Doppler plane of the true targets and false targets. Finally, we evaluate the performance of the proposed method as well as achieve a good trade-off between anti-jamming performance and computational complexity via numerical simulations. [ABSTRACT FROM AUTHOR]

This paper proposes a novel modulation algorithm based on vector decomposition and model predictive control for 5-level active neutral-point-clamped (5 L-ANPC) inverter. Firstly, the control of 5-level inverter is transformed into that of 3-level inverter by vector decomposition, which reduces the control complexity. Secondly, based on the framework of 3-level inverter, the optimal zero sequence voltage and switch state sequence are selected by multi-objective optimisation of model predictive control to balance the neutral point voltage and floating capacitors voltages simultaneously. Finally, according to the optimal choice, single-carrier comparison is used to generate the drive signal, which does not require traditional dual-carrier or vector synthesis, and is relatively easy to implement. Experimental results verify the validity of the method. [ABSTRACT FROM AUTHOR]

In this paper, modelling and hardware implementation of three-phase interleaved inverter-based shunt active power filter (SAPF) is proposed to mitigate current harmonics, reactive power for ensuring unity power factor and load balancing without shoot-through effect. Shoot-through effect is one of the hazardous issues in conventional voltage source inverters such as damage of power electronic switches, electromagnetic interference, ringing in the power circuitry. The present power system has inevitable non-linear loads which create large variations in the supply voltage distortions. Therefore, the compensation capability and efficiency of the SAPFs degrades. A novel predictive tuned filter is proposed in this paper to estimate the variations in the amplitude of supply voltage, frequency and harmonics for extracting the fundamental voltage signal. The fundamental extracted signal is further processed for reference current generation using generalized p-q theory. The performance of the proposed system is simulated using MATLAB®/Simulink environment and tested under different supply voltage conditions. The simulation results have been validated by developing a prototype in the laboratory by using a dSPACE1104 controller. It is found from the simulated and experimental results that the proposed system is fast, robust and accurate which improves the power quality without shoot-through problem. [ABSTRACT FROM AUTHOR]

This paper has discussed the study of the performance of dynamic voltage restorer (DVR) taking different voltage sag conditions in the supply voltage of the distribution system for linear and non-linear load. DVR is employed to mitigate the voltage sag. Proportional and integral (PI) controller is used for the control of DVR to mitigate the voltage sag. Synchronous reference frame theorybased control algorithm has been implemented for generating reference voltages. In this paper, an efficient improved particle swarm optimisation technique for optimizing the gain parameters of the PI controller has been proposed. The performance and suitability of DVR is validated through MATLAB simulation results and use of Sim Power Systems Blocksets. Integral squared error is implemented to check the performance and suitability of DVR. Extensive results of the proposed method are presented and compared with conventional Ziegler Nichols and genetic algorithm methods of tuning gain parameters of PI controllers. [ABSTRACT FROM AUTHOR]

The main challenge of Cognitive Radio (CR) is to identify the occurrence of primary users (PU) effectively to mitigate interference with licenced communications. The occurrence of PU is identified by spectrum sensing (SS). Due to shadowing and deep fading, SS may produce false sensing results. Cooperative spectrum sensing (CSS) can mitigate these problems but at the cost of extra energy consumption especially when the CR users are battery functioned. In CSS, the fusion rule directly affects the energy efficiency (EE) of CR users, it can be optimised to increase EE. Moreover, the energy consumption of the CR users can be minimised if they are grouped into clusters. In this paper intra and inter fusion schemes have been proposed in a cluster-based CSS (CB-CSS). The overall EE is maximised by optimising the inter and intra fusion rule threshold of CB-CSS. An iterative algorithm has been presented that determines the optimal value of inter and intra fusion rule. Results show that for 6X6cluster size, optimum inter and intra fusion rule threshold is found to be 4 and 5, respectively. [ABSTRACT FROM AUTHOR]

Advancement in CMOS technology demands to revamp the design of basic functional units in digital systems. The binary addition is the basic operation in digital units like microprocessors, digital signal processors and data processing units in ASICs. Scaling down the technology no longer supports power density and energy-efficient digital architectures. The energy-efficient adder design demands the exploration of recurrence structures, existing algorithms, circuit design techniques, system constraints, energy and delay trade-offs. This paper presents the systematic design approach towards the design of an energy-efficient 64-bit parallel-prefix adder. A novel two-bit sum block reduces the power dissipation and the proposed recurrence algorithm further optimises the overall energy consumption. The 64-bit adder is implemented in static CMOS design and simulated in 45, 32, 22 and 16 nm technology nodes to validate the energy efficiency. In 45 nm technology, the proposed 64-bit parallel-prefix adder consumes 64.61% and 15.3% less energy compared to Brent–Kung and Ling adder respectively whereas in 16 nm technology, the proposed adder consumes 57.54% lesser energy than Brent–Kung adder and 14.28% lesser energy compared to the Ling adder. [ABSTRACT FROM AUTHOR]

In this paper an integrated hybrid converter topology, unique DC input as well as at same time of outputs DC and AC that use a hybrid control method. At established integrated converter, accomplish high step up voltage and implement outputs of DC as well as AC to greater reliability, switching topology is utilised. The established hybrid strategy is joint execution of spotted hyena optimiser (SHO) and random forest algorithm (RFA), therefore, it called as SHORFA method. In proposed strategy, SHO is utilised to optimise combination of the controller parameters based on the voltage variation. In light of the optimal datasets, the RFA gives the optimal switching pulses of the driver. The RFA learning process is improved to utilise SHO algorithm at aspect of objective function as minimal error. By the established converter design, voltage stress over diodes as well as power switch is lessened. Additionally, the proposed converter directs the output voltage, power factor correction, reduces the voltage spikes over the switches and restrains the switching losses. The proposed strategy performed at worksite of MATLAB/Simulink platform compared to various existing methods. [ABSTRACT FROM AUTHOR]

There are few available approaches for time delay estimation (TDE) which offer with a potential to be implemented as real-time-embedded systems. Most of these lose accuracy in reverberant and highly noisy environments. In this paper, we initially proposed a 2-dimensional (2D) signal based on the cross-correlation. Then, we proposed two approaches for TDE, based on this 2D signal. There are two main advantages for using the proposed approaches. The first merit is that using a large amount of information about the correlation between the received signals allows a more robust TDE against noise and reverberation, when compared to the other possible techniques. The second one is that the number of samples to calculate the TDE algorithms is decreasing significantly, which is reducing the computational complexity. This paper also proposes a feasible hardware structure to implement the proposed approaches on digital signal processor embedded systems in real time. [ABSTRACT FROM PUBLISHER]

Due to the unknown nature of the mechanical loads, proper tuning of the speed controllers is always a serious challenge in servo motor drives. The problem becomes more complicated when the speed signal feedback is received from the conventional sensors such as incremental encoders which are prone to the quantisation erros. This could basically result in creation of unwanted noise during the closed-loop speed regulation process. To mitigate the problem, this paper proposes a superior offline tuning method for the speed controllers as compared with the conventional approaches. The bandwidth is calculated in a way that the fluctuation of the reference torque is limited to a given percentage of the motor-rated torque, which leads to lower acoustic noise. In addition, an offline detection algorithm is proposed to estimate the mechanical features of the load. In this method, two new auxiliary mechanical parameters are defined for the motor-load set and estimated using a computationally efficient approach. The estimated mechanical features as well as the bandwidth value are used to calculate optimal gains for the speed controller. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive normalised subband adaptive filtering (NSAF) to accomplish the betterment of NSAF performance. In the proposed NSAF, an extended adaptiveness is introduced from its variants in two ways. In the first way, the step-size is set adaptive, and in the second way, the selection of subbands is set adaptive. Hence, the proposed NSAF is termed here as variable step-size-based NSAF with selected subbands (VS-SNSAF). Experimental investigations are carried out to demonstrate the performance (in terms of convergence) of the VS-SNSAF against the conventional NSAF and its state-of-the-art adaptive variants. The results report the superior performance of VS-SNSAF over the traditional NSAF and its variants. It is also proved for its stability, robustness against noise and substantial computing complexity. [ABSTRACT FROM AUTHOR]

Wireless mesh network (WMN) forms a wireless backbone framework for multi-hop transmission among the routers and clients in the extensible coverage area. To improve the throughput of WMNs with multiple gateways (GWs), several issues related to GW selection, load balancing and frequent link failures due to the presence of dynamic obstacles and channel interference should be addressed. This paper presents a novel cross-layer fault tolerant and load balancing (CFTLB) protocol to overcome the issues in WMN. Initially, the neighbour GW is searched and channel load is calculated. The GW having least channel load is selected which is estimated during the arrival of the new node. The proposed algorithm finds the alternate GWs and calculates the channel availability under high loading scenarios. If the current load in the GW is high, another GW is found and channel availability is calculated. Besides, it initiates the channel switching and establishes the communication with the mesh client effectively. The utilisation of hashing technique in proposed CFTLB verifies the status of the packets and achieves better performance in terms of router average throughput, throughput, average channel access time and lower end-to-end delay, communication overhead and average data loss in the channel compared to the existing protocols. [ABSTRACT FROM AUTHOR]

This paper proposes a Takagi–Sugeno (T–S) fuzzy method to select cost function weights of finite control set model predictive DC–DC converter control algorithms. The proposed method updates the cost function weights at every sample time by using T–S type fuzzy rules derived from the common optimal control engineering knowledge that a state or input variable with an excessively large magnitude can be penalised by increasing the weight corresponding to the variable. The best control input is determined via the online optimisation of the T–S fuzzy cost function for all the possible control input sequences. This paper implements the proposed model predictive control algorithm in real time on a Texas Instruments TMS320F28335 floating-point Digital Signal Processor (DSP). Some experimental results are given to illuminate the practicality and effectiveness of the proposed control system under several operating conditions. The results verify that our method can yield not only good transient and steady-state responses (fast recovery time, small overshoot, zero steady-state error, etc.) but also insensitiveness to abrupt load or input voltage parameter variations. [ABSTRACT FROM PUBLISHER]

The distributed modulated wideband converter (DMWC) is a kind of sub-Nyquist sampling system which randomly moves the sparse wideband signal spectrum to the baseband to realise low-speed sampling. DMWC regards each sensor node as a sampling channel and combines compressed sensing technology with a broadband cooperative spectrum sensing network. However, DMWC contains phase and transmission attenuation, which results in joint sparsity destroyed. Therefore, the original signal cannot be reliably recovered. In this paper, we combine measurement matrix with a phase shift to develop a phase shift calibration algorithm (PSCA) based on DMWC, a calibration matrix that is constructed to eliminate the influence of phase shift on recovery rate. Firstly, random waveforms of different channels in the DMWC system correspond to the row vectors of the measurement matrix. We apply the frequency-domain method to construct a calibration matrix. Secondly, we estimate the phase shift in each channel and write it as a complex diagonal matrix. Finally, we consider balancing the phase shift in each channel, the phase shift of each channel multiplied by the corresponding row of the measurement matrix. Theoretical analysis and numerical simulations show that the algorithm improves the recovery rate to 98% or higher in lower SNR. [ABSTRACT FROM AUTHOR]

Cognitive radio technology is a solution to the spectrum scarcity problem that exists in today's wireless networks. It provides spectrum conscious paradigm. However, these wireless systems impose eccentric challenges because of dynamic spectrum availability and diverse quality of service requirements. This paper investigates the performance of the adaptive cognitive system in multi-user and multi-channel environment. Since the system has to work in such a hostile environment, to enhance the performance of the system, modified joint rate and power adaptation algorithm is proposed. The novel packet-based water-filling power adaptation (PBWFPA) algorithm proposed in this treatise defines power per packet. The channel environment is consisting of multi-path fading channels TGn-A (Throughput task group-A) and TGn-D (Throughput task group-D). The adaptation algorithm considers interweave scheme in the performance evaluation of the cognitive system. The transmitter adapts transmit parameters based on channel state information (CSI) and soft information regarding activities of the primary users in the cognitive environment. The transmit parameters are computed at the receiver end and fed to the transmitter through the feedback channel. The simulation results reflect significant improvement in the throughput of the system even in an opportunistic channel-sharing environment. Higher-quality channel selection ensures the enhancement in the throughput of the system. [ABSTRACT FROM AUTHOR]

In this paper, direction of arrival (DOA) estimation of multiple signals with coprime array is investigated and signal subspace fitting (SSF) method is linked to the coprime array, which achieves a better DOA estimation performance than the traditional uniform array. While the SSF method requires expensive computational cost in the case of multiple signals due to the multidimensional global angular searching, we propose a successive SSF (S-SSF) algorithm from a computationally efficient perspective. In the proposed algorithm, we employ rotational invariance and coprime property to obtain the initial estimates. Then, via a successive scheme, we transform the traditional multidimensional global angular searching problem into one-dimensional partial angular searching one. Consequently, the computational complexity has been significantly reduced. Specifically, the proposed S-SSF algorithm can obtain almost the same DOA estimation performance as SSF but with remarkably lower complexity. Finally, Cramer-Rao Bound (CRB) is provided and numerical simulations demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper introduces a split-capacitor shunt Active Power Filter (SC-APF) based on Synchronous Reference Frame (SRF) theory. This topology is used in compensating the currents of 3-Ph unbalanced non-linear loads. The voltage control loop used in SRF which is only suitable in controlling Four-Leg APF (FL-APF) is modified to control Spilt-Capacitor APF (SC-APF). The proposed scheme provides compensating the 3-Ph unbalanced non-linear loads with lower number of switches, passive elements, and sensors. The performance of the SC-APF with the modified calculation algorithm is verified through simulation and experimental studies. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach for flywheel replacement of Induction Motor (IM) with convenient power electronic circuitry. Methology: The proposed technique is the joined execution of the Salp Swarm Optimization Algorithm (SSA) plus Adaptive Neuro-Fuzzy Interference System (ANFIS) based duty ratio controller. Findings: In the proposed technique, the ANFIS procedure is enhanced by using the SSA algorithm with regards to the minimum error objective function. Here, the inverter switching states are updated by the proposed approach by constraining the error between the setpoint torque and the demand torque to the extended target work. With this proposed technique, unbalance between the demand torque and the generated torque is found with high precision and snappier execution. It is used to haul pull out the torsional pulsation in touchy load-connected transmission systems. Result: The execution of the proposed technique is actualized in the MATLAB/Simulink platform and compared with the existing methods. [ABSTRACT FROM AUTHOR]

With the aggressive scaling of integrated circuit technology, parametric estimation is a critical task for designers who looked for solutions to the challenges of some Nanoscale CMOS parameters. This paper presented the prediction of primary parameters of CMOS transistor for 16 nm to 10 nm process nodes using both of Bisquare Weights (BW) method and a novel recursive least squares (RLS) parameter estimation algorithm. The proposed RLS algorithm consists of the minimisation of a quadratic criterion relating to the prediction error in order to attain the best estimated parameters of the developed mathematical model. The obtained results thanks to the proposed RLS algorithm were better than those reached using the BW method. Comparisons between Predictive Technology Model (PTM) data and parameters estimated with RLS algorithm were made to check the validity and the consistency of the proposed algorithm. These predicted primary parameters were helpful to estimate and to optimise the performances of the Variable Gain Amplifier (VGA) which was a basic circuit element with a key role in the design of new upcoming receivers. [ABSTRACT FROM AUTHOR]

A new digit serial GF(2m) multiplier based on the dual basis representation is presented for the first time in this paper. The multiplier is suitable for large word lengths such as those found in cryptosystems. Digit serial computations give a much better trade-off between area and speed in comparison with bit-parallel realization, which is too costly, and bit-serial realization which is too slow. The new multiplier is based on a look-ahead technique which serves to overcome the recursive algorithm used to calculate the extra elements of the operand represented in the dual basis prior to the multiplication process. This recursive algorithm is the main bottleneck for digit-serial multiplication. Unlike existing design, the new multiplier has low latency, and its digit size is not restricted by the type of primitive polynomial being used. A systolic version of the new multiplier, suitable for VLSI implementation, is also presented. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the effect of service differentiation on the power consumption in contention period of IEEE 802.15.4 sensor networks. Power consumption is analysed for two different service differentiation schemes under non-saturation condition. The two service differentiation schemes are the differentiation by the backoff exponent (BED) and differentiation by the contention window (CWD), which provide multilevel differentiated services in beacon-enabled mode with slotted carrier sense multiple access/collision avoidance (CSMA/CA) algorithm. The analysis is based on the stationary probabilities of a discrete-time Markov chain, which is a model of CSMA/CA describing the state of a head packet of a device. Numerical results show that CWD uses the power more efficiently and performs better in terms of throughput, while BED more differentiates the service. [ABSTRACT FROM AUTHOR]

This paper presents a hardware authentication BLAKE algorithm based on physical unclonable functions (PUFs) in Taiwan Semiconductor Manufacturing Company low-power 65 nm CMOS. To support hardware authentication feature, PUFs have been organised in BLAKE algorithm as the salt value. The trials table method is used to improve the robust of PUFs, resulting in approximately 100% stability against supply voltage variations form 0.7 V to 1.6 V. By discussing the G-function of BLAKE algorithm, the hardware implementation is considered for acceleration, resulting in significant performance improvements. The die occupies 2.62 mm2and operates maximum frequency 1.0 GHz at 1.6 V. Measured results show that PUFs have great random characteristic and the authentication chip dissipates an average power of 91 mW under typical condition at 1.2 V and 780 MHz. In comparison with other works, the PUFs-based BLAKE algorithm has hardware authentication feature and improves throughput about 45%. [ABSTRACT FROM AUTHOR]

This paper discusses a new possible encryption scheme that provides more support necessary to protect communications between emitter and receiver, using the general diagonal and column matrix burst correcting code and a pseudorandom sequence (PN). An essential definition is given for an algorithm (the distance factor). Implementation of the algorithm can be carried out and tested easily with data. Also the paper presents a new practical method for a dynamic encryption operating system. [ABSTRACT FROM AUTHOR]

The biggest challenge of the traditional 3D orthogonal matching pursuit (OMP) method for direction-of-departure (DOD), direction-of-arrival (DOA) and Doppler frequency estimation in bistatic multiple-input multiple-output (MIMO) radar is the heavy computational burden due to a large number of atoms in the overcomplete dictionary. In this paper, low complexity 3D-OMP algorithms are investigated. First, the traditional 3D-OMP algorithm is given. Then, two-dimensionality reduced OMP-based algorithms are proposed exploiting the property of Khatri-Rao product and proper sparse representation. Also, the multiple measurement vectors (MMV) model is introduced to our OMP algorithms to guarantee the estimation performance. The simulation results show that the DOD, DOA and Doppler frequency can be effectively estimated with a small number of pulses and low computation cost. With similar accuracy compared with the traditional 3D-OMP method, much lower computational burden can be achieved by using the proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, a blind signal separation (BSS) methodology for simultaneously received multisystem frequency-overlapped signals in a single-channel (SC) electromagnetic surveillance system is proposed using fast independent component analysis (FastICA) in a dynamical embedding (DE) framework. Firstly, an appropriate DE matrix is constructed out of a series of delay vectors from the SC recording. The lag-time and the dimensional of embedding matrix setting principal are introduced in details. Next, multiple independent components (ICs) are calculated by decomposing the embedding matrix through FastICA algorithm, and ICs can be regarded as a convenient expansion basis of the original signals. Then, these ICs are projected back into the measurement space. After that, these projected ICs are classified and used for recovering the sources of interest based on their independent nature and their power density spectrum. Numerical simulation results obtained in evaluating the proposed methodology’s performance confirmed the effectiveness of the proposed algorithm. [ABSTRACT FROM PUBLISHER]

This paper discusses the problem of coherent direction of arrival (DOA) estimation in a monostatic multi-input multi-output (MIMO) radar using a single pulse, and proposes a reduced dimension (RD)-estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. We reconstruct the received data and then utilise it to construct a set of Toeplitz matrices. After that, we use RD-ESPRIT to obtain the DOAs of the sources. The proposed algorithm is effective for coherent angle estimation based on a single pulse, and it has much better angle estimation performance than the forward backward spatial smoothing (FBSS)-ESPRIT algorithm and the ESPRIT-like of Li, as well as very close angle estimation performance to the ESPRIT-like of Han. For complexity comparison, our algorithm has very close complexity to the FBSS-ESPRIT algorithm, and lower complexity than the ESPRIT-like of Han and the ESPRIT-like of Li. Simulation results present the effectiveness and improvement of our approach. [ABSTRACT FROM PUBLISHER]

Multicarrier code division multiple access (MC-CDMA) system is one of the most effective techniques in fourth-generation (4G) wireless technology, due to its high data rate, high spectral efficiency and resistance to multipath fading. However, MC-CDMA systems are greatly deteriorated by carrier frequency offset (CFO) which is due to Doppler shift and oscillator instabilities. It leads to loss of orthogonality among the subcarriers and causes intercarrier interference (ICI). Water filling algorithm (WFA) is an efficient resource allocation algorithm to solve the power utilisation problems among the subcarriers in time-dispersive channels. The conventional WFA fails to consider the effect of CFO. To perform subcarrier power allocation with reduced CFO and to improve the capacity of MC-CDMA system, residual CFO compensated adaptive subcarrier power allocation algorithm is proposed in this paper. The proposed technique allocates power only to subcarriers with high channel to noise power ratio. The performance of the proposed method is evaluated using random binary data and image as source inputs. Simulation results depict that the bit error rate performance and ICI reduction capability of the proposed modified WFA offered superior performance in both power allocation and image compression for high-quality multimedia transmission in the presence of CFO and imperfect channel state information conditions. [ABSTRACT FROM AUTHOR]

Location information of sensor nodes is of vital importance for most applications in wireless sensor networks (WSNs). This paper proposes a new range-free localisation algorithm using support vector machine (SVM) and polar coordinate system (PCS), LSVM-PCS. In LSVM-PCS, two sets of classes are first constructed based on sensor nodes’ polar coordinates. Using the boundaries of the defined classes, the operation region of WSN field is partitioned into a finite number of polar grids. Each sensor node can be localised into one of the polar grids by executing two localisation algorithms that are developed on the basis of SVM classification. The centre of the resident polar grid is then estimated as the location of the sensor node. In addition, a two-hop mass-spring optimisation (THMSO) is also proposed to further improve the localisation accuracy of LSVM-PCS. In THMSO, both neighbourhood information and non-neighbourhood information are used to refine the sensor node location. The results obtained verify that the proposed algorithm provides a significant improvement over existing localisation methods. [ABSTRACT FROM AUTHOR]

A robust time delay estimation (TDE)-based direction-finding method for multipath signals in the presence of impulsive noise is proposed in this paper. Compared to traditional algorithms, developed for Gaussian distribution, this method performs more robust in the presence of non-Gaussian noise. The robust TDE is first obtained by utilising the matched filtering in-space which is less sensitive to outliers. Then direction-of-arrival (DOA) is estimated by ‘steering vector fitting’ approach based on the delay estimates. An iterative approach is employed to estimate each multipath component separately and improve the estimation accuracy. The method is developed in-space, which minimises the-norm of residual fitting error vector instead of the Frobenius norm. The number of antennas required can be less than that of the sources. Simulation results show that the method outperforms several outliers-resistant algorithms both in cases of impulsive noise and Gaussian distribution noise. [ABSTRACT FROM AUTHOR]

Proportional to absolute temperature (PTAT) current sources are one of the most important building blocks in analogue circuit design. An important PTAT current source is the Meijer all-NPN cross-quad circuit, where the PTAT output current does not present a strong dependence on the bias current and requires only four matched transistors to be realised, being adequate to be implemented with discrete circuits. In this paper, we present a technique that improves the performance of the Meijer cross-quad PTAT current source and minimises the deviations from the ideal behaviour by simply adding two transistors and adjusting the cell bias voltage. Simulated results in the -40 C to 85°C temperature range show that the errors were reduced by two orders of magnitude by using the novel technique, and a maximum non-linearity of 0.44 ppm/°C was obtained. A prototype of the circuit was built using the LM3046 transistor array, and a maximum deviation from the PTAT ideal current of only 0.06% was measured in 0–80°C, while in the conventional PTAT circuit an error of 0.81% was measured. [ABSTRACT FROM AUTHOR]

This paper presents an efficient design of digital finite impulse response (FIR) filter, based on polyphase components and swarm optimisation techniques (SOTs). For this purpose, the design problem is formulated as mean square error between the actual response and ideal response in frequency domain using polyphase components of a prototype filter. To achieve more precise frequency response at some specified frequency, fractional derivative constraints (FDCs) have been applied, and optimal FDCs are computed using SOTs such as cuckoo search and modified cuckoo search algorithms. A comparative study of well-proved swarm optimisation, called particle swarm optimisation and artificial bee colony algorithm is made. The excellence of proposed method is evaluated using several important attributes of a filter. Comparative study evidences the excellence of proposed method for effective design of FIR filter. [ABSTRACT FROM PUBLISHER]

Most of the research on identifying and classifying signal models is limited to single signals such as AM, QAM or PSK, and there is a lack of research on the parameters of the identified signals. To make up for this deficiency, an OA (Optimality Confidence and Amplitude Ratio factor) algorithm model is proposed to identify and classify 13 kinds of modulation signals, including 2 kinds of analogue modulation signals (AM and FM), 11 kinds of signal digital modulation (M-SK and M-QAM). Based on the characteristics of the constellation diagram, Confidence and Amplitude Ratio factors are constructed to identify and classify signals with different parameters such as 'Format", "Centre Frequency" and "Sample Rate' and different modulation types. In addition, because of the mis-judgement and confusion problems in identifying classification signals, a three-layer optimisation algorithm is proposed to optimise the OA algorithm model. Numerical simulation results show that the comprehensive identification efficiency of the proposed optimisation algorithm is increased by 18.84%. [ABSTRACT FROM AUTHOR]

The instruction-set extensions problem has been one of the major topics in recent years and it consists of the addition of a set of new complex instructions to a given instruction-set. This problem in its general formulation requires an exhaustive search of the design space to identify the candidate instructions. This search turns into an exponential complexity of the solution. In this paper we propose an efficient linear complexity algorithm for the automatic generation of convex multiple input multiple output instructions, whose convexity is theoretically guaranteed. The proposed approach is not restricted to basic-block level and does not impose limitations either on the number of input and/or output, or on the number of new instructions generated. Our results show a significant overall application speedup (up to ×2.9 for ADPCM decoder) considering the linear complexity of the proposed solution and which therefore compares well with other state-of-art algorithms for automatic instruction-set extensions. [ABSTRACT FROM AUTHOR]

Float-point to fixed-point conversion is required by many communication, voice and image applications, in order to achieve acceptable levels of performance and cost. This is particularly crucial in real-time applications that have strict timeline requirement on processing throughput and latency. Therefore, fixed-point conversion from float-point computation brings great challenges with the improvement at the same time: How to evaluate the accuracy of the fixed-point system quickly? This paper proposes a novel method for the float-point to fixed-point conversion and evaluates the precision of complex signal systems from statistical perspective. The proposed approach greatly reduces the complexity of the evaluation, and achieves optimum fixed-point implementation in a short time. The experiments in MP3 and the AAC decoding algorithm demonstrate that the accuracy of the fixed-point system is greatly improved by this method. [ABSTRACT FROM AUTHOR]

This paper presents a hardware-efficient memory allocation technique, called EMA, that detects the existence of any free block of requested size in memory. EMA can allocate a free memory block of any number of chunks in any part of memory without having any internal fragmentation. The gate-level design of the hardware unit, along with its area-time measurements is given in this paper. Simulation results indicate that EMA is fast and flexible enough to allocate/deallocate a free block in any part of memory resulting in efficient utilization of memory spaces. In addition, the VHDL synthesis with FPGA implementation shows that EMA has less complicated hardware, and is faster than the known hardware techniques. [ABSTRACT FROM AUTHOR]

Multiple-valued logic (MVL) synthesis is a problem that has attracted increased interest in recent years. The MVL synthesis problem is more involved compared to its binary counterpart. The search space for finding optimal MVL functional synthesis is enormous. Conventional deterministic methods for MVL functional synthesis are prohibitively expensive, indicating an eminent need for the use of iterative heuristic-based synthesis techniques. In this paper, an ant colony optimization (ACO) based heuristic algorithm for synthesis of MVL functions is proposed. The algorithm mimics the ants' behaviour in the real world. Real ants are found to be able to select the shortest path between their nest and food sources in the existence of alternate paths, or even hurdles between the two. The proposed ACO algorithm uses some of the known real ant techniques in finding the shortest paths to the (near) optimal number of product terms that can cover the minterms of a given MVL function. The proposed algorithm is tested using 50 000 randomly generated 2-variable 4-valued functions. The results obtained using the proposed approach show that the proposed approach outperforms existing direct cover (DC) techniques in terms of the average number of product terms (implicants) required to synthesize a given MVL function. [ABSTRACT FROM AUTHOR]

In this paper a fast algorithm of partial matrix elimination (PME) combined with a new strategy of variable time step (VTS) is developed for transient analysis of nonlinear circuits containing interconnects. In PME the admittance matrix in the MNA equation of circuit analysis is arranged to consist of two submatrices. The lower submatrix, which contains contributions of only linear elements, is constant for a fixed time step and is partially triangulated by Gauss elimination for several time step values picked out by the new VTS strategy. At each Newton iteration, Gauss elimination is needed only for the upper submatrix, which contains contributions of nonlinear devices. PME with the new strategy of VTS is faster and more accurate than traditional Gauss elimination (TGE) with VTS for circuit analysis. Moreover, the efficiency of circuit optimization can be improved with PME. [ABSTRACT FROM AUTHOR]

This paper describes the development of computable and accurate approximate expressions for the conditional law of a diffusion process observed in continuous time which satisfy the Zakai equation and solve the nonlinear filtering problem. The proposed numerical algorithm makes it possible to shift offline the most time-consuming operations. In comparison with the extended Kalman filter (EKF) it is more robust in the case of high signal-to-noise ratio (i.e. low measurement noise intensity). The estimation accuracy of the proposed algorithm increases when the process noise intensity increases. It is readily implementable on a digital computer and gives a sample pathwise solution. Using the Galerkin technique, the solution of the Zakai equation is approximated by means of a sequence of nonstandard basis functions given by a parametrized family of trigonometric Fourier series. For illustration, some numerical examples are solved using the proposed algorithm and the EKF. [ABSTRACT FROM AUTHOR]

In this paper, the two-dimensional electron gas (2DEG) concentration is numerically calculated for single and double heterostructure band profiles by solving Schrödinger's and Poisson's equations self-consistently. An expected energy level is introduced to enhance the speed of calculation in obtaining quantized energy levels through the iteration process. Conventional AlGaAs/GaAs and AlGaAs/InGaAs/GaAs structures are selected to prove the validity of this calculation. Three different concentrations, namely, positively ionized donors, free electrons in the conduction band and 2DEG, are considered through the band profiles. Both the 2DEGs in the narrow bandgap and free electrons in the wide bandgap have been calculated and compared with the data available in the literature. Furthermore, positively ionized donors are also obtained and correlated with 2DEG and free electrons to predict the gate capacitance characteristics of the devices, and showed good agreement with the experimental data. [ABSTRACT FROM AUTHOR]

Symbolic circuit analysis provides the key for understanding the mechanisms underneath circuit operation, and it can be used to obtain predictive models of circuit behaviour. Symbolic analysis has many applications in the design of analogue circuits but is severely limited by the size of the resulting expressions. Thus an efficient approximation strategy is required for successful symbolic analysis of large analogue circuits. A fully symbolic procedure for the simplification of large expressions, which mimics the heuristic procedures followed by an experienced designer (based on the relations between the parameters of the circuit), is presented in this paper. This simplification strategy is particularly well suited to be combined with some circuit level partition algorithms, leading to a blend between simplification after generation (SAG) and simplification during generation (SDG). The algorithms have been implemented and integrated on a prototype software package for the automated analysis and design of analogue circuits. [ABSTRACT FROM AUTHOR]

In this paper we propose a ΣΔ-digital-to-analogue converter (DAC) architecture using a clock from an all-digital fractional programmable clock generator as an oversampling clock. Although this method is attractive in respect of implementation issues, it has not been widely used because the clock generated by this method contains a significant amount of jitter. The proposed architecture uses an edge-selection algorithm to suppress the in-band noise caused by the oversampling clock jitter. The improvement of the algorithm over the previous work is mainly achieved by adopting a second-order four-way edge selection. Simulation results show that the improved algorithm achieves a signal-to-noise distortion ratio of around 100dB when applied to a 1-bit ΣΔ-DAC for a voiceband codec and that the performance degradation due to the clock jitter has been kept within 3dB. [ABSTRACT FROM AUTHOR]

Performance of direction of arrival (DOA) estimation is significantly degraded in practical situations. One of the conditions that decreases its performance, is the coherent loss caused by the propagation of the wavefront through random non-homogeneous media. Most of the previous methods, such as matrix fitting method and covariance matching technique, need the multidimensional search; therefore their computations are difficult and not suitable for a real-time application. In this paper, a three-stage method based on the generalised eigenvalues utilising signal subspace eigenvectors (GEESE) and Gauss–Newton (GN) algorithms, namely 3SM/GE-GN, is presented. Simulation results show the effectiveness of the proposed method. Difference of RMSE of DOA estimation between proposed method, which is independent of the coherent loss, and other methods is more clearly visible in higher snapshots. As well, in fixed snapshot, the RMSE of the proposed method is lower than others in different SNRs. Furthermore, the computational time of the simulation is very lower than two previous works. [ABSTRACT FROM AUTHOR]

Many problems in adaptive filtering can be approached from the point of view of system identification. For an adaptive filter with N adjustable coefficients or weights, the mean-squared value of the output error is a plot, in N + 1 dimensions, of the mean-squared error versus the N coefficient values. If the adaptive filter is non-recursive, the mean-squared value of the output error is a quadratic function of the coefficients. With recursive adaptive filters, the output error is not quadratic and may even have local minima. This paper introduces a new class of adaptive recursive algorithm, which offer a much reduced computational load for basically the same performance, and has a non-vanishing gain which enables the algorithm to remain active and to track time-varying systems. A simplified version of the algorithm, called the steepest descent recursive algorithm, which retains provable convergence at low convergence rates, is well suited to system identification. [ABSTRACT FROM AUTHOR]

Previous papers by the same authors have considered methods for solving a 3 x 3 system and a partitioned system of 3n x 3n linear equations which are suitable for an environment of nine transputers. This paper covers the case of a general n x n system of linear equations. The new algorithm is fully described in an Occam-like language. The number of flops in the parallel and the sequential media are compared. A numerical example for solving a 4 x 4 system is given. [ABSTRACT FROM AUTHOR]