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There are two challenges for efficient processing of both the sliding spotlight and terrain observation by progressive scans (TOPS) data using full-aperture algorithms. First, to overcome the Doppler spectrum aliasing, zero-padding is required for azimuth up sampling, increasing the computation burden; second, the azimuth deramp operation for avoiding synthetic aperture radar (SAR) image folding leads to azimuth time shift along the range dimension, and in turn the appearance of ghost targets and azimuth resolution reduction at the scene edge, especially in the wide-swath case. In this paper, a novel three-step algorithm is proposed for processing the sliding spotlight and TOPS data. In the first step, a modified derotation is derived in detail based on the chirp z-transform (CZT), avoiding zero-padding; then, the chirp scaling algorithm kernel is adopted for precise focusing in the second step; and in the third step, instead of the traditional range-independent deramp, a range-dependent deramp is applied to compensate for the time shift. Moreover, the SAR image geometry distortion caused by range-dependent deramp is corrected by employing a range-dependent CZT. Experimental results based on both simulated data and real data are provided to validate the proposed algorithm. [ABSTRACT FROM PUBLISHER]

A novel framework is proposed for mitigating azimuth ambiguities in spaceborne stripmap synthetic aperture radar (SAR) images. The azimuth ambiguities in SAR images are localized by using a local mean SAR image, SAR system parameters, and a defined metric derived from azimuth antenna pattern. The defined metric helps isolate targets lying at locations of ambiguities. The mechanism for restoration of ambiguity regions is selected on the basis of size of ambiguity regions. A compressive imaging technique is employed to restore isolated ambiguity regions (smaller regions of interconnected pixels), whereas clustered regions (relatively bigger regions of interconnected pixels) are filled by using exemplar-based inpainting. The simulation results on a real TerraSAR-X data set demonstrated that the proposed scheme can effectively remove azimuth ambiguities and enhance SAR image quality. [ABSTRACT FROM PUBLISHER]

Integrating spatial information into hyperspectral unmixing procedures has been shown to have a positive effect on the estimation of fractional abundances due to the inherent spatial-spectral duality in hyperspectral scenes. However, current research works that take spatial information into account are mainly focused on the linear mixing model. In this paper, we investigate how to incorporate spatial correlation into a nonlinear abundance estimation process. A nonlinear unmixing algorithm operating in reproducing kernel Hilbert spaces, coupled with a l1-type spatial regularization, is derived. Experiment results, with both synthetic and real hyperspectral images, illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper presents a method for identifying a set of dense subgraphs of a given sparse graph. Within the main applications of this “dense subgraph problem,” the dense subgraphs are interpreted as communities, as in, e.g., social networks. The problem of identifying dense subgraphs helps analyze graph structures and complex networks and it is known to be challenging. It bears some similarities with the problem of reordering/blocking matrices in sparse matrix techniques. We exploit this link and adapt the idea of recognizing matrix column similarities, in order to compute a partial clustering of the vertices in a graph, where each cluster represents a dense subgraph. In contrast to existing subgraph extraction techniques which are based on a complete clustering of the graph nodes, the proposed algorithm takes into account the fact that not every participating node in the network needs to belong to a community. Another advantage is that the method does not require to specify the number of clusters; this number is usually not known in advance and is difficult to estimate. The computational process is very efficient, and the effectiveness of the proposed method is demonstrated in a few real-life examples. [ABSTRACT FROM PUBLISHER]

Inspired by Weber's Law, this paper proposes a simple, yet very powerful and robust local descriptor, called the Weber Local Descriptor (WLD). It is based on the fact that human perception of a pattern depends not only on the change of a stimulus (such as sound, lighting) but also on the original intensity of the stimulus. Specifically, WLD consists of two components: differential excitation and orientation. The differential excitation component is a function of the ratio between two terms: One is the relative intensity differences of a current pixel against its neighbors, the other is the intensity of the current pixel. The orientation component is the gradient orientation of the current pixel. For a given image, we use the two components to construct a concatenated WLD histogram. Experimental results on the Brodatz and KTH-TIPS2-a texture databases show that WLD impressively outperforms the other widely used descriptors (e.g., Gabor and SIFT). In addition, experimental results on human face detection also show a promising performance comparable to the best known results on the MIT+CMU frontal face test set, the AR face data set, and the CMU profile test set. [ABSTRACT FROM AUTHOR]

In this paper, the effect of rise time (200 ns and 2 μs, respectively) of rectangular pulse on the inactivation of Staphylococcus aureus has been studied. Apple juice with three different conductivities (1.5 mS/cm, 2.0 mS/cm, and 2.5 mS/cm) was inactivated 75 μs at an electric field strength of 25 kV/cm, 30 kV/cm, and 35 kV/cm, respectively. The experiment results showed that the pulse with shorter rise time had higher effect of inactivation and lower solution temperature increases after treatment, and the difference between te inactivation effects was more than 0.5 logs in general. Fast Fourier transform analysis showed that the pulse with shorter rise time had higher amplitude of low frequencies and more high-frequency components, which resulted in a higher transmembrane potential of Staphylococcus aureus cells and higher effect on intracellular material. [ABSTRACT FROM AUTHOR]

This paper focuses on the adaptive robust control (ARC) for servomechanisms whose dynamic models are subject to unknown parameters, disturbance, and parameter sudden changes. To improve the control performance of the traditional ARC, a novel identifier-based ARC (IFARC) scheme is proposed. In this scheme, an identifier is utilized to accelerate the parameter tuning process and to heighten the accuracy of parameter estimation. A switching logic component based on a given performance index is introduced to select the better parameter estimate vector from those provided by the identifier and the adaptation law. As a result, transient performance can be improved according to the certainty equivalence principle. In addition, the exact reconstruction of the unknown parameters and exponential decay of the tracking error can be achieved under certain conditions. The stability and performance of IFARC are theoretically analyzed. Finally, simulation results show that the IFARC can achieve favorable tracking performance. [ABSTRACT FROM AUTHOR]

The work is motivated by real-world applications of detecting Adverse Drug Reactions (ADRs) from administrative health databases. ADRs are a leading cause of hospitalization and death worldwide. Almost all current postmarket ADR signaling techniques are based on spontaneous ADR case reports, which suffer from serious underreporting and latency. However, administrative health data are widely and routinely collected. They, especially linked together, would contain evidence of all ADRs. To signal unexpected and infrequent patterns characteristic of ADRs, we propose a domain-driven knowledge representation Unexpected Temporal Association Rule (UTAR), its interestingness measure, unexlev, and a mining algorithm MUTARA (Mining UTARs given the Antecedent). We then establish an improved algorithm, HUNT, for highlighting infrequent and unexpected patterns by comparing their ranks based on unexlev with those based on traditional leverage. Various experimental results on real-world data substantiate that both MUTARA and HUNT can signal suspected ADRs while traditional association mining techniques cannot. HUNT can reliably shortlist statistically significantly more ADRs than MUTARA (p = 0.00078). HUNT, e.g., not only shortlists the drug alendronate associated with esophagitis as MUTARA does, but also shortlists alendronate with diarrhoea and vomiting for older (age ≥ 60) females. We also discuss signaling ADRs systematically by using HUNT. [ABSTRACT FROM AUTHOR]

In this paper, an optical simulation-based lithography hotspot fix guidance generator and an automatic hotspot fix flow are proposed. We develop our aerial image simulation engine by enhancing the traditional sum of coherence system method. Subject to the shape changes, a strong correlation between the aerial image intensity difference maps of pre-optical proximity correction (OPC) and post-OPC schemes is found. We collect near a litho hotspot in a pre-OPC layout some fix actions that are local shape changes to optimize the optical intensity. Then, fix guidances will be selected from the collected fix actions by a heuristic algorithm and input to a router for fixing the hotspot. We integrate the fix guidance generation method with a commercial lithography hotspot detection tool to create an automatic post-route optical-simulation-embedded local fix (OSELF) flow and test with industry 65 nm designs. Compared with the commercial flow that uses only local fix, our method has a 1.4x-1.9x fix rate, similar run time, no new design rule check violation, and negligible circuit timing impacts. We also combine our OSELF algorithm with a rip-up and reroute engine, and test on the same designs. Compared to the commercial tool that uses a hybrid (local fix plus reroute) fix flow, our combined flow runs 1.7x-2.9x faster with 45-55% circuit timing impact. Both flows achieve a 100% hotspot fix rate. [ABSTRACT FROM AUTHOR]

This paper presents the design, fabrication, and characterizations of a flip-chip-bonded micromachined capacitor for tuning a high-temperature superconductive resonator. The major issue of the tunable superconductive resonator is its high driving voltage due to the accumulated thermal stresses and the sensitivity of the superconductive material to the fabrication process. The tunable capacitor in the form of a microbridge with flexible boundaries is proposed to reduce thermal stress. Thermal stress is reduced to 10 MPa, and the pull-in voltage of the capacitor is 25 V. The micromachined capacitor and the superconductive resonator are fabricated separately and then integrated together by using a flip-chip-bonding technique. This integration method prevents the superconductor material from the high-temperature process. At 75-K operation temperature, the measured center frequency of the fabricated tunable resonator changes from 2.93 to 2.87 GHz when the driving voltage increases from 0 to 40 V. [ABSTRACT FROM AUTHOR]

This paper takes an in-depth look at a technique for computing filtered matrix-vector (mat-vec) products which are required in many data analysis applications. In these applications, the data matrix is multiplied by a vector and we wish to perform this product accurately in the space spanned by a few of the major singular vectors of the matrix. We examine the use of the Lanczos algorithm for this purpose. The goal of the method is identical with that of the truncated singular value decomposition (SVD), namely to preserve the quality of the resulting mat-vec product in the major singular directions of the matrix. The Lanczos-based approach achieves this goal by using a small number, of Lanczos vectors, but it does not explicitly compute singular values/vectors of the matrix. The main advantage of the Lanczos-based technique is its low cost when compared with that of the truncated SYD. This advantage comes without sacrificing accuracy. The effectiveness of this approach is demonstrated on a few sample applications requiring dimension reduction, including information retrieval and face recognition. The proposed technique can be applied as a replacement to the truncated SVD technique whenever the problem can be formulated as a filtered mat-vec multiplication. [ABSTRACT FROM AUTHOR]

Global optimization process can often be divided into two subprocesses: exploration and exploitation. The tradeoff between exploration and exploitation (T:Er&Ei) is crucial in search and optimization, having a great effect on global optimization performance, e.g., accuracy and convergence speed of optimization algorithms. In this paper, definitions of exploration and exploitation are first given based on information correlation among samplings. Then, some general indicators of optimization hardness are presented to characterize problem difficulties. By analyzing a typical contraction-based three-stage optimization process, Optimal Contraction Theorem is presented to show that T:Er&Ei depends on the optimization hardness of problems to be optimized. T:Er&Ei will gradually lean toward exploration as optimization hardness increases. In the case of great optimization hardness, exploration-dominated optimizers outperform exploitation-dominated optimizers. In particular, random sampling will become an outstanding optimizer when optimization hardness reaches a certain degree. Besides, the optimal number of contraction stages increases with optimization hardness. In an optimal contraction way, the whole sampling cost is evenly distributed in all contraction stages, and each contraction takes the same contracting ratio. Furthermore, the characterization of optimization hardness is discussed in detail. The experiments with several typical global optimization algorithms used to optimize three groups of test problems validate the correctness of the conclusions made by T:Er&Ei analysis. [ABSTRACT FROM AUTHOR]

This paper proposes a novel nonparametric approach for the modeling and analysis of electricity price curves by applying the manifold learning methodology—locally linear embedding (LLE). The prediction method based on manifold learning and reconstruction is employed to make short-term and medium-term price forecasts. Our method not only performs accurately in forecasting one-day-ahead prices, but also has a great advantage in predicting one-week-ahead and one-month-ahead prices over other methods. The forecast accuracy is demonstrated by numerical results using historical price data taken from the Eastern U.S. electric power markets. [ABSTRACT FROM AUTHOR]

A key process in assembly of microelectromechanical systems optical switches is of inserting fibers into U-grooves in silicon substrate. Due to positioning errors and dimensional tolerances in components, heavy collision occurs between fibers and the edges of U-grooves during insertion, throwing out fibers from the fiber holder or worse, damaging the components. Typical solutions to the problem involve determining errors using machine vision or force sensors, and then positioning fibers accurately by virtue of high precision multi-axis systems (with submicron repeatability). However, these approaches are costly and difficult to implement. In this paper, we present a low-cost passive assembly method to solve the problem. It utilizes a special flexure-based fixture to regulate high contact forces and accommodate assembly errors. Specifically, we model the problems happening in the process of fiber insertion and characterize the conditions of successful insertion. We then suggest how to design flexural fixtures so that the required insertion conditions can be met. Experimental results show that using such a fixture the fiber assembly can be successfully implemented even if the assembly system's accuracy is lower than 12 µm in x and y axes, and 0.07° in theta axis. These requirements are within the reach of most low-cost precision systems. Note to Practitioners—In the assembly of optical switches, heavy collision occurs during inserting fiber into U-grooves due to positioning errors and dimensional tolerances in components. It may result in fiber skidding out from the gripper, or the component damage. This paper aims to present a low-cost but effective method to solve the problem. The idea is utilizing a special "floating" fixture that can self-regulate high contact forces and accommodate assembly errors. This fixture is designed with flexures. In practical application, it can be built either as a standalone component or as an embedded mechanism built-in on the chip. Preliminary physical experiments show by adopting such a fixture, fibers can be inserted into U-grooves without any skidding and damage even if using normal pick-and-place systems. [ABSTRACT FROM AUTHOR]

As a large-scale database of hundreds of thousands of face images collected from the Internet and digital cameras becomes available, how to utilize it to train a well-performed face detector is a quite challenging problem. In this paper, we propose a method to resample a representative training set from a collected large-scale database to train a robust human face detector. First, in a high-dimensional space, we estimate geodesic distances between pairs of face samples/examples inside the collected face set by isometric feature mapping (Isomap) and then subsample the face set. After that, we embed the face set to a low-dimensional manifold space and obtain the low-dimensional embedding. Subsequently, in the embedding, we interweave the face set based on the weights computed by locally linear embedding (LLE). Furthermore, we resample nonfaces by Isomap and LLE likewise. Using the resulting face and nonface samples, we train an AdaBoost-based face detector and run it on a large database to collect false alarms. We then use the false detections to train a one-class support vector machine (SVM). Combining the AdaBoost and one-class SVM-based face detector, we obtain a stronger detector. The experimental results on the MIT + CMU frontal face test set demonstrated that the proposed method significantly outperforms the other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The sparse representation of a multiple-measurement vector (MMV) is a relatively new problem in sparse representation. Efficient methods have been proposed. Although many theoretical results that are available in a simple case—single-measurement vector (SMV)—the theoretical analysis regarding MMV is lacking. In this paper, some known results of SMV are generalized to MMV. Some of these new results take advantages of additional information in the formulation of MMV. We consider the uniqueness under both an l0-norm-like criterion and an l1-norm-like criterion. The consequent equivalence between the l0-norm approach and the l1-norm approach indicates a computationally efficient way of finding the sparsest representation in a redundant dictionary. For greedy algorithms, it is proven that under certain conditions, orthogonal matching pursuit (OMP) can find the sparsest representation of an MMV with computational efficiency, just like in SMV. Simulations show that the predictions made by the proved theorems tend to be very conservative; this is consistent with some recent advances in probabilistic analysis based on random matrix theory. The connections will be discussed. [ABSTRACT FROM AUTHOR]

Presents a study that investigated the tracking properties of linear shift-invariant feedback control systems. Examination of the tracking performance problem pertaining to a vector version of the step signal; Analysis of the tracking performance for real sinusoids and unit ramp signals; Limitations of tracking performance in time-delay systems.

Studies the asymptotic properties of Η[sub*infin] identification problems and algorithms. Divergence of untuned linear algorithms; Application of triangle inequality; Sample complexity of an identification problem.

In this paper, we propose a vertical transistor with n-bridge and body on gate (BOG-DRAM) for Low-power 1T-DRAM application. The vertical channel of the device can reduce the short-channel effect and improve scalability. The storage region stacked on the gate leads to the efficient utilization of storage space. The device with junctionless channel layers on three sides can improve writing time. The conventional current bridge device only has one side gatecontrol depletion region, but the proposed BOG-DRAM has triple-side gate-control depletion region which can improve programming window at shorter gate lengths. BOG-DRAM achieves programming window of 33.6 μA/μm when the storage length is 20 nm. In addition, the work function offset is exploited for low-power application. [ABSTRACT FROM AUTHOR]

Two challenges have been faced in signal processing of ultrahigh-resolution spaceborne synthetic aperture radar (SAR). The first challenge is constructing a precise range model, and the second one is to develop an efficient imaging algorithm since traditional algorithms fail to process ultrahigh-resolution spaceborne SAR data effectively. In this paper, a novel high-order imaging algorithm for high-resolution spaceborne SAR is presented. First, a modified equivalent squint range model (MESRM) is developed by introducing equivalent radar acceleration into the equivalent squint range model, and it is more suitable for high-resolution spaceborne SAR. The signal model based on the MESRM is also presented. Second, a novel high-order imaging algorithm is derived. The insufficient pulse-repetition frequency problem is solved by an improved subaperture method, and accurate focusing is achieved through an extended hybrid correlation algorithm. Simulations are performed to validate the presented algorithm. [ABSTRACT FROM PUBLISHER]

The polar format algorithm (PFA) is a wavenumber domain imaging method for spotlight synthetic aperture radar (SAR). The classic fixed-parameter PFA employs interpolation technique for data correction. However, such an operation will induce heavy computational load and cause degradation in computation precision. To optimize image formation processing performance, this study presents a novel parameter-adjusting PFA, which can implement SAR image formation at an extremely highly squint angle with obviously improved computation efficiency and imaging precision. In the parameter-adjusting PFA, radar parameters, such as center frequency, chirp rate, pulse duration, sampling rate, and pulse repeat frequency (PRF), vary for each azimuth sampling position. Due to the parameter adjusting strategy, the echoed signal can be acquired directly in keystone format with uniformly distributed azimuth intervals. In this case, range interpolation, which is necessary in the fixed-parameter PFA to convert data from polar format to keystone format, can be eliminated. Chirp z-transform (CZT) can be employed to focus SAR data along the azimuth direction. Compared with truncated sinc-interpolation, CZT was found to perform better in inducing less phase and amplitude errors in data processing. When residual video phase (RVP) compensation was accomplished for dechirped signal, the processing steps of the parameter-adjusting PFA were simplified as azimuth CZTs and range inverse fast Fourier transforms (IFFT). Lastly, computer simulation of multiple point targets validated the presented approach. [ABSTRACT FROM AUTHOR]

A variable-bit look-ahead Huffman decoding problem is investigated in this paper. The objective is to maximize the decoding throughput rate by exploiting different equivalent state diagrams. The decoding throughput rate is estimated based on the state transition probability of the corresponding Huffman encoding table. We propose an efficient algorithm to search for a heuristic solution that usually yields very good optimization results in polynomial computation time. [ABSTRACT FROM AUTHOR]

A novel networked multisensor data-fusion method is developed in this paper. A federated filter is employed to fuse the data transmitted over the network, which plays an important role in the data-processing center. The stability of filters under the network is considered; an algorithm to deal with the delayed data is introduced, and the principle for data fusion is presented. Finally, two numerical examples show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

The design problem of networked control systems (NCS) with constant and random network delay in the forward and feedback channels, respectively, is considered in this paper. A novel networked predictive control (NPC) scheme is proposed to overcome the effects of network delay and data dropout. Stability criteria of closed-loop NPC systems are presented. The necessary and sufficient conditions for the stability of closed-loop NCS with constant time delay are given. Furthermore, it is shown that a closed-loop NPC system with bounded random network delay is stable if its corresponding switched system is stable. Both simulation study and practical experiments show the effectiveness of the control scheme. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel joint algorithm to estimate the symbol timing and carrier frequency offsets of wireless orthogonal frequency division multiplexing (OFDM) signals. To jointly estimate synchronization parameters using the maximum likelihood (ML) criterion, researchers have derived conventional models only from additive white Gaussian noise (AWGN) or single-path fading channels. We develop a general ML estimation algorithm that can accurately calculate symbol timing and carrier frequency offsets over a fast time-varying multipath channel. To reduce overall estimation complexity, the proposed scheme consists of two estimation stages: coarse and fine synchro nizations. A low complexity coarse synchronization based on the least-squares (LS) method can rapidly estimate the rough symbol timing and carrier frequency offsets over a fast time-varying multipath channel. The subsequent ML fine synchronization can then obtain accurate final results based on the previous coarse synchronization. Simulations demonstrate that the coarse-to-fine method provides a good tradeoff between estimation accuracy and computational complexity. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel framework for fast multilevel routing considering crosstalk and performance optimization. To handle the crosstalk minimization problem, we incorporate an intermediate stage of layer/track assignment into the multilevel routing framework. For performance-driven routing, we propose a novel minimum-radius minimum-cost spanning tree heuristic for global routing. Compared with the state-of-the-art multilevel routing with the routability mode, the experimental results show that our router achieved a 6.7X runtime speedup, reduced the respective maximum and average crosstalk (coupling length) by about 30% and 24%, reduced the respective maximum and average delay by about 15% and 5%. Compared with the timing-driven mode, the experimental results show that our router still achieved a 5.9X runtime speedup, reduced the respective maximum and average crosstalk by about 35% and 23%, reduced the respective maximum and average delay by about 7% and 10% in comparable routability, and resulted in fewer failed nets. [ABSTRACT FROM AUTHOR]

Proposes a three-step net-even-wiring system to complete the routing of the bond pads to the corresponding grid pins on one or more layers of a pin grid array (PGA) microchip package. Overview of the routing model; Experimental results; Conclusion.

This paper develops a novel algorithm, termed SPARse Truncated Amplitude flow (SPARTA), to reconstruct a sparse signal from a small number of magnitude-only measurements. It deals with what is also known as sparse phase retrieval (PR), which is NP-hard in general and emerges in many science and engineering applications. Upon formulating sparse PR as an amplitude-based nonconvex optimization task, SPARTA works iteratively in two stages: In stage one, the support of the underlying sparse signal is recovered using an analytically well-justified rule, and subsequently a sparse orthogonality-promoting initialization is obtained via power iterations restricted on the support; and in the second stage, the initialization is successively refined by means of hard thresholding based gradient-type iterations. SPARTA is a simple yet effective, scalable, and fast sparse PR solver. On the theoretical side, for any n-dimensional k-sparse (k ≪ n) signal x with minimum (in modulus) nonzero entries on the order of (1/√k)||x||2, SPARTA recovers the signal exactly (up to a global unimodular constant) from about k2 log n random Gaussian measurements with high probability. Furthermore, SPARTA incurs computational complexity on the order of k2 n log n with total runtime proportional to the time required to read the data, which improves upon the state of the art by at least a factor of k. Finally, SPARTA is robust against additive noise of bounded support. Extensive numerical tests corroborate markedly improved recovery performance and speedups of SPARTA relative to existing alternatives. [ABSTRACT FROM AUTHOR]

The research on vital information extraction meets a lot challenges due to the narrow bandwidth and low signal-to-noise ratio of a vital sign in real environment. In this paper, a novel noncontract vital sign detection method based on multiple higher order cumulant is presented. According to the characteristic of vital sign for impulse ultrawideband radar, the quasi-periodic reflected echo in slow-time is analyzed. The novel method is theoretically deduced from fourth-order cumulant. It is proved to be better than the reference fast Fourier transform method by simulation and experiment. By using the new method, the range position and frequency information of life can be extracted accurately and automatically. [ABSTRACT FROM AUTHOR]

Gabor features have been known to be effective for face recognition. However, only a few approaches utilize phase feature and they usually perform worse than those using magnitude feature. To investigate the potential of Gabor phase and its fusion with magnitude for face recognition, in this paper, we first propose local Gabor XOR patterns (LGXP), which encodes the Gabor phase by using the local XOR pattern (LXP) operator. Then, we introduce block-based Fisher's linear discriminant (BFLD) to reduce the dimensionality of the proposed descriptor and at the same time enhance its discriminative power. Finally, by using BFLD, we fuse local patterns of Gabor magnitude and phase for face recognition. We evaluate our approach on FERET and FRGC 2.0 databases. In particular, we perform comparative experimental studies of different local Gabor patterns. We also make a detailed comparison of their combinations with BFLD, as well as the fusion of different descriptors by using BFLD. Extensive experimental results verify the effectiveness of our LGXP descriptor and also show that our fusion approach outperforms most of the state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

An RF front-end transceiver is implemented in standard 0.18-µm CMOS for V2.1 Bluetooth applications. All signal detection and gain calibrations are realized without the need of baseband control, but using an incoming Gaussian frequency-shift keying signal detection mechanism, auto low-noise amplifier gain mode selection, and autogain calibration with a combined programmable gain amplifier/received-signal-strength indicator function. Moreover, a simple control interface between transceiver and baseband is designed. The differential error vector magnitude performance of the transmitter is less than 6%, and a less than 7.5-dB system noise figure is achieved in the receiver. Continuous current consumptions in receiver and transmitter are 32 and 42 mA, respectively, with a 1.8-V internal regulator voltage. [ABSTRACT FROM AUTHOR]

This paper describes the difference between normal microlenses and zero-space microlenses in image sensors. The investigation of both sensitivity and crosstalk has been implemented for normal microlenses and zero-space microlenses that are fabricated on a 2.8-µm pinned photodiode array of 640 (row) by 480 (column) based on an 0.18-µm-CMOS process. The simulation results show that the zero-spacemicrolens technology increases the pixel sensitivity by about 75.61% and decreases the crosstalk by about 9.4% compared to the normal microlens technology. This paper presents the sensitivity analysis of both normal microlenses and zero-space microlenses based on the wafer test data from the Teradyne IP750, which is a special wafer test platform for CMOS sensors. The results of the statistical data of the wafer test show that the sensitivity of the zero-space microlenses has been improved by about 73.6% on the red pixel (69.6% on the green pixel and 76.3% on the blue pixel) compared with that of the normal microlenses. Using a similar statistical method, the crosstalk characteristics of both the zero-space microlenses and the normal microlenses have been measured as well. Compared with the normal microlenses, the testing results show that the crosstalk of green light in red light is reduced by about 7.244% and the crosstalk of blue light in red light is reduced by about 41.447% due to the use of the zero-space microlens technology. More importantly, this paper also provides the comparison and analysis of the real images taken by CMOS image sensors with the normal microlenses and the zero-space microlenses, respectively. From the comparison of image results, the image luminance of the zero-space microlenses is higher than that of the normal microlenses, and the image definition of the zero-spacemicrolenses is clearer than that of the normal microlenses as well. So far, the silicon results show that the zero-space microlens technology is a better choice than the normal microlens technology for CMOS image sensors of a small-size pixel. [ABSTRACT FROM AUTHOR]

Nano electromechanical systems (NEMS) represent an important new class of device with wide ranging applications. In this paper we report proposals and calculations for novel methods for excitation and readout of cantilever-style NEMS resonators which are applicable over a wide temperature range. We suggest a Lorentz force-based excitation method and discuss an ultrasensitive readout provided by a nanoSQUID, where the cantilever vibration modulates the inductance of the nanoSQUID loop, allowing potentially sub-picometer amplitude sensitivity to be achieved. [ABSTRACT FROM AUTHOR]