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Space-time block codes (STBCs) from coordinate interleaved orthogonal designs (CIODs) offer several advantages including full-diversity and single-symbol decodability. In an effort to assess their performance in quasi-static frequency-nonselective i.i.d. Nakagami-m fading channels, we analyze the error rate, outage capacity, and information outage probability. First, based on an accurate closed-form formula for the average symbol pairwise error rate (SPER), we derive tight union upper and lower bounds on the symbol-error rate (SER). Second, we apply Gaussian and Gamma approximations to provide closed-form expressions for the outage capacity. Third, using high signal-to-noise ratio (SNR) and moment-matching approximation techniques, we also derive accurate closed-form approximations for the information outage probability (IOP). Finally, we show that STBCs from CIODs provide full-diversity by deriving SER-based and IOP-based asymptotic and instantaneous diversity orders. Monte-Carlo simulations show that the analytical results agree with simulation experiments. Index Terms--Space-time block codes (STBCs), coordinate interleaved orthogonal designs (CIODs), Nakagami-m fading, symbol-error rate, mutual information, outage capacity, information outage probability, asymptotic diversity order.

We analyze the effect of time-selective fading on the information outage probability and diversity order of Alamouti transmit diversity with joint maximum likelihood, symbolwise linear maximum likelihood, zero forcing, and decision feedback detectors. In contrast to the existing bit error rate (BER) and bit error outage (BEO) analyses, we evaluate the information outage probabilities and corresponding asymptotic diversity orders for each detector. From the theoretical and simulation results, we demonstrate that, when the channel is time selective, the asymptotic diversity orders for the four detectors approach two, zero, one, and one, respectively. Index Terms--Alamouti transmit diversity, asymptotic diversity order, information outage probability, mutual information, time-selective fading channel.

This paper develops a signal processing, time-frequency analysis-based analytic solution to locate transient capacitor switching disturbances. The flow of transient disturbance energy caused by the capacitor switching is determined by the time and frequency localized phase difference. Cross time-frequency analysis provides time-and frequency-localized phase difference between the transient voltage and current disturbance waveforms which determine the direction of transient disturbance energy flow. The time and frequency localization properties of the proposed scheme allows one to expand the application to complicated power distribution systems without knowledge of system parameters, capacitor size, and configuration. The proposed scheme has been verified by the Electromagnetic Transients Program simulation for all possible spatial locations of the capacitor switching. Index Terms--Capacitor switching disturbance, cross time-frequency analysis, direction finder, power quality, time-frequency analysis.

The influence of damage on the performance of the lifting surface of an aircraft has been an area of interest to the military for over half a century. Some of the earlier studies of this subject focused on the impact that structural damage resulting in the loss of lifting surface structural strength, stiffness, and mass might have on imparting catastrophic aeroelastic failures to the lilting surface. Discouraging mixed results arose over the next 30 years in these investigations that employed only structural damage models. As time passed, it was finally noticed that if the often neglected, usually second-order, drag term was now included (as aerodynamic damage often creates a high, unsteady, localized drag rise) in the earlier aeroelastic damaged-wing analyses, more encouraging results were obtained. That is, the realistic asymmetric damaged lifting surfaces flutter and divergence analysis did show lowered, and not raised, flutter and divergence speeds over that of the undamaged lilting surface. This occurred both in the presence of or in the absence of structural damage as in the case of icing or external wing stores. In essence, it was determined at this time that the resulting high and unsteady drag rise caused by the damage could do more than just cause an energy deficiency in the aircraft mission. It could, in fact, cause shorter term catastrophic or stiffness failure events in terms of reduced flutter and divergence speeds as well as give rise to limit cycle oscillations embedded within what was shown to be that part of the damaged-aircraft flight envelope free from classic flutter and divergence. The present experimental wind-tunnel study was carried out to confirm these past theoretical findings by employing a one-twelfth-scale F-111 aeroelastic model and (third-order) higher-order statistical signal processing to identify the frequency ordering that occurs in these additional damaged-induced limit cycle oscillations. These limit cycle oscillations were also found to exhibit the classic lock-in/lock-out phenomenon that occurs in the well-known F/A-16 and F/A-18 wing store induced limit cycle oscillations.

A framework for the exploitation of a general non-redundant precoding for blind channel estimation in multiple-input-muliple-output (MIMO) block transmission systems with a cyclic prefix (CP) is presented. Findings reveal the achievement of accurate channel estimation with a small number of symbol blocks.

By combining multiple-input multiple-output (MIMO) communication with the orthogonal frequency division multiplexing (OFDM) modulation scheme, MIMO-OFDM systems can achieve high data rates over broadband wireless channels. In this paper, to provide a bandwidth-efficient solution for MIMO-OFDM channel estimation, we establish conditions for channel identifiability and present a blind channel estimation technique based on a subspace approach. The proposed method unifies and generalizes the existing subspace-based methods for blind channel estimation in single-input single-output OFDM systems to blind channel estimation for two different MIMO-OFDM systems distinguished according to the number of transmit and receive antennas. In particular, the proposed method obtains accurate channel estimation and fast convergence with insensitivity to overestimates of the true channel order. If virtual carriers (VCs) are available, the proposed method can work with no or insufficient cyclic prefix (CP), thereby potentially increasing channel utilization. Furthermore, it is shown under specific system conditions that the proposed method can be applied to MIMO-OFDM systems without CPs, regardless of the presence of VCs, and obtains an accurate channel estimate with a small number of OFDM symbols. Thus, this method improves the transmission bandwidth efficiency. Simulation results illustrate the mean-square error performance of the proposed method via numerical experiments. Index Terms--Blind channel estimation, cyclic prefix, multiple-input multiple-output (MIMO) system, orthogonal frequency division multiplexing (OFDM), subspace method, virtual carrier.

This paper proposes a new switched MIMO system where the MIMO includes both diversity-based MIMO and spatial multiplexing MIMO (SM-MIMO). The proposed scheme is a closed-loop system where the feedback bits are sent back to the transmitter to indicate the channel quality. The switching operation is employed among groups of a certain number of transmit antennas. For diversity-based MIMO systems, the switching operation aims to improve the link performance, while the goal of the switching for the SM-MIMO systems is to increase the data rate. The authors analyze and optimize the proposed systems and show that there is considerable benefit in terms of performance and practical use. Index Terms--Diversity techniques, fading channels, MIMO, performance analysis, switched diversity, transmit diversity.

For reasonable power quality assessment of transient disturbances in electric power systems, new transient power quality indices are developed based on a signal processing technique, time-frequency analysis. Based on the time-frequency distribution of a transient disturbance, a set of time-frequency based power quality indices are developed. In this paper, the instantaneous disturbance energy ratio, normalized instantaneous disturbance energy ratio, instantaneous frequency, and instantaneous K-factor are suggested for transient power quality assessment. Time-frequency based power quality indices allow one to quantify the effects of transient disturbances with high-resolution and accuracy. Index Terms--Instantaneous disturbance energy ratio, instantaneous frequency, instantaneous K-factor, normalized instantaneous disturbance energy ratio, power quality, power quality index, time-frequency analysis, transient disturbance.

Recently, ultra wide-band (UWB) wireless communication technology, which provides high data transmission rates and is capable of linearly trading off between throughput and signal-to-noise ratio (SNR), has drawn much attention for short-range wireless networks. To fully exploit its desirable features and to minimize its interference with coexisting other systems requires knowledge of the SNRs at the receivers. In this paper, we propose an algorithm for estimating the pulse energy-to-noise ratio of an UWB signal through utilization of output samples from a correlator in the receiver and evaluate the performance of the proposed algorithm through computer simulation. A notable feature of the proposed algorithm is that it does not affect the effective throughput because the estimation process does not require any additional specific training signals. Index Terms--Correlator outputs, pulse energy to noise ratio, signal-to-noise ratio (SNR) estimation, ultra wide-band (UWB) wireless communication system.

In conventional discrete multitone (DMT) systems, a multitap time-domain equalizer (TEQ) is used to shorten the channel length, so that the bandwidth efficiency reduction due to cyclic extension is relieved. The TEQ, however, tends to introduce spectral nulls which degrade the achievable signal-to-noise ratio at corresponding subchannels, thereby decreasing the bandwidth efficiency. Furthermore, computationally expensive joint TEQ initialization and optimal delay (introduced by TEQ) selection is necessary. In this paper, a novel subsymbol-equalization scheme is proposed, and is based on the observation that the high-bit-rate twisted-pair channels rarely contain a zero that is close to the unit circle. Although a delay of a fraction of a DMT symbol period is introduced, the proposed subsymbol-equalization scheme eliminates the necessity of both the channel shortening at the receiver and the cyclic extension at the transmitter. Simulation results demonstrate the computational efficiency (no TEQ) and the handwidth efficiency of the proposed subsymbol-equalization scheme. Index Terms--Channel shortening, discrete multitone (DMT), equalization.

In this paper, the effects of visual feedback and aging on postural sway systems and signals are investigated by analyzing the transient phase difference between 'input' and 'output' which correspond to center of pressure (COP) and center of mass (COM), respectively. In order to analyze the transient phase difference characteristics of COP and COM, a relatively new cross time-frequency analysis technique that provides time-and frequency-localized phase difference information is utilized. The feedback control process in the postural sway is interpreted in terms of a feedback compensator which is characterized in terms of a phase difference. Using the experimental results of the transient phase difference obtained from the cross time-frequency distribution, it is demonstrated that the postural control of young persons are more stable and rely more on visual sensory feedback to stabilize postural control compared to that of the elderly persons. Index Terms--Aging, cross time-frequency distribution, feedback control, phase difference spectrum, postural sway, time-frequency analysis, visual sensory system.

The Volterra series representation of Cohen's class of time-frequency distributions is examined. The analogy of the bilinear class with a second-order double Volterra series is utilized.

This paper presents a novel classification method for power distribution line disturbances using a rule-based method and a wavelet packet-based hidden Markov model (HMM). The rule-based method is utilized for the classification of time-characterized-feature disturbances, and the wavelet packet-based HMM is utilized for the frequency-characterized-feature power disturbances. This proposed method classifies six types of actual recorded power distribution disturbances, i.e., sag, interruption, fast capacitor switching, capacitor switching, normal variation, and impulse disturbance, and obtains 98.7 % correct classification rate for 670 actual disturbance events tested. Index Terms--Classifier, hidden Markov model (HMM), power disturbances, wavelet packet.

A Volterra predistorter, based on an indirect learning architecture, is more effective in improving the performance of telecommunication channels than a pth-order Volterra predistorter. The indirect Volterra series model has a simpler design, as compared to the pth-order inverse method. The indirect Volterra predistorter can compensate for channel nonlinearities without determining a pth-order Volterra model of the nonlinear channel and inverting the pth-order. The optimization of the design helps in reducing the number of higher order nonlinearities to be generated.

A fast frequency-domain algorithm utilizes 2-D and 3-D overlap-save methods, and a 1-D fast Fourier transform to evaluate time-domain output of a third order Volterra filter. The computational steps are lesser than the time-domain multidimensional convolution procedure. The sectioning techniques of the overlap-save method generate the linear time-domain output convolution. Moreover, the algorithm can be reduced to quadratic filters or extended to higher order filters. The complexity of this algorithm is compared with that of the multidimensional convolution procedure.

In this paper we present a new approach to detect, localize, and investigate the feasibility of classifying various types of power quality disturbances. The approach is based on wavelet transform analysis, particularly the dyadic-orthonormal wavelet transform. The key idea underlying the approach is to decompose a given disturbance signal into other signals which represent a smoothed version and a detailed version of the original signal. The decomposition is performed using multiresolution signal decomposition techniques. We demonstrate and test our proposed technique to detect and localize disturbances with actual power line disturbances. In order to enhance the detection outcomes, we utilize the squared wavelet transform coefficients of the analyzed power line signal. Based on the results of the detection and localization, we carry out an initial investigation of the ability to uniquely characterize various types of power quality disturbances. This investigation is based on characterizing the uniqueness of the squared wavelet transform coefficients for each power quality disturbance. Keywords - Power quality disturbances, wavelet transform analysis, multiresolution signal decomposition, uniqueness search.

In this paper a practical and efficient method is presented for the counting of third-order products generated by an arbitrary number of carriers with arbitrary power spectral shapes. In particular, three selective counting procedures (i.e., sorting by position, sorting by position and group, and sorting by position, group, and kind) are introduced in a systemic way, based upon a discrete third-order Volterra model. The advantage of the counting algorithm is that 1) the algorithm provides the exact counting of third-order products of all eleven possible groups; 2) the counting process requires only two multiplications for the selective counting of third-order products at each position, and the algorithm, which is thus efficient, can be easily implemented.

Polybenzimidazole (PBI) and polysulfone (PS) do not form miscible blends; however, the tensile modulus and strength of their blend fibers are comparable to, or better than, that of PBI fibers, depending on process conditions. Fibers spun from an 80/20 PBI/PS solution blend have PBI-like LOI (limiting oxygen indices) and flame shrinkage behavior. Sulfonation and stabilization of this fiber improve its thermal properties. The process window for these blend fibers has been determined. There was no aging phenomenon on as-spun PBI/PS blend fibers, while as-spun fibers made from PBI/polyarylate (PA) and PBI/high modulus aramides (HMA) exhibited remarkable aging effects on fiber properties. This difference probably arises from the fact that 1) the former is not a miscible blend, while the latter are; and 2) the former does not have hydrolysis groups, such as ester and amide groups, as that in the PA and HMA systems.

Second-order harmonic and intermodulation distortion of nonlinear systems such as audio components are derived using a digital spectral technique wherein the system was characterised by Volterra kernels. The random input approach was compared to the two-tone input method in terms of the quadratic transfer function. The assumption of Gaussianity in nonlinear system identification experiments is also shown to be a misrepresentation.

A new algorithmic method estimates Volterra kernels of cubic systems having zero-mean i.i.d. signal inputs. A simple real matrix is used, and this reduces the complexity as compared to non-i.i.d or non-Gaussian input cases. Correlation moments of higher orders are converted into moments around the origin, enabling simple real matrices for a zero-mean i.i.d. signal input.

While existing techniques are capable of automatically identifying and classifying various types of distribution-level power quality disturbances, they do not provide any information about the locations of the disturbance sources. This paper shows that it is possible to use sampled voltage and current waveforms to determine on which side of a recording device a disturbance originates. This is accomplished by examining the energy flow and peak instantaneous power for both capacitor energizing and voltage sag disturbances. We demonstrate the technique by testing it on both ATP-generated waveforms and actual field disturbance data. In both cases, we are able to accurately determine on which side of a recording device the disturbance originates. If enough recording devices are available in a network, the individual readings can be collectively used to pinpoint the locations of disturbance sources. Index Terms--Capacitor switching, direction finder, disturbance locator, power quality, voltage sag.

A scalable event identification system for power quality events is proposed. Unlike ANN-based approaches where the system is not scalable and not 'debug-able' without retraining, the proposed approach is particularly advantageous compared to those of ANN's since it is scalable, debug-able and easily modified. This approach is adopted from artificial intelligence's rule-based approach and attempts to mimic power engineers thought process in identifying PQ events. This paper describes prerequisites in constructing such a scalable system. Examples of rules to identify power quality event are also presented. The prototype of the system is built and tested using 770 field-measured voltage waveforms which covers ten types of PQ events. The accuracy rate is nearly 95% with less than 6% of rejection rate. Potential applications of the proposed system in PQ community are also described. Index Terms--ANN, power quality, rule-based system, scalable.

It is the objective of this paper to present unique features that characterize power quality events and methodologies to extract them from recorded voltage and/or current waveforms using Fourier and wavelet transforms. Examples of unique features include peak amplitudes, RMS, frequency, and statistics of wavelet transform coefficients. These features are derived from well documented theories, power engineers' heuristics gained through long years of experience, and power quality data collected in recent years. Converter operation, transformer energization, and capacitor energization (which includes normal, back-to-back, and restrike on opening energization), representing three common power quality events at the distribution level, are presented. These examples provide the basis for further characterization of other power quality events. Index Terms--Fourier and wavelet transforms, identifying features, power quality.

A wavelet-based neural classifier is constructed and thoroughly tested under various conditions. The classifier is able to provide a degree of belief for the identified waveform. The degree of belief gives an indication about the goodness of the decision made. It is also equipped with an acceptance threshold so that it can reject ambiguous disturbance waveforms. The classifier is able to achieve the accuracy rate of more than 90% by rejecting less than 10% of the waveforms as ambiguous. Index Terms--Automatic classification and identification, Dempster-Shafer theory of evidence, power quality disturbance, voting scheme.

Existing techniques for recognizing and identifying power quality disturbance waveforms are primarily based on visual inspection of the waveform. It is the purpose of this paper to bring to bear recent advances, especially in wavelet transforms, artificial neural networks, and the mathematical theory of evidence, to the problem of automatic power quality disturbance waveform recognition. Unlike past attempts to automatically identify disturbance waveforms where the identification is performed in the time domain using an individual artificial neural network, the proposed recognition scheme is carried out in the wavelet domain using a set of multiple neural networks. The outcomes of the networks are then integrated using decision making schemes such as a simple voting scheme or the Dempster--Shafer theory of evidence. With such a configuration, the classifier is capable of providing a degree of belief for the identified disturbance waveform. Index Terms--Artificial neural networks, Dempster-Shafer theory of evidence, pattern recognition, power quality, voting scheme, wavelet transforms.