Presented is a new measuring and reconstruction framework of Compressed Sensing (CS), aiming at reducing the measurements required to ensure faithful reconstruction. A sparse vector is segmented into sparser vectors. These new ones are then randomly sensed. For recovery, we reconstruct these vectors individually and assemble them to obtain the original signal. We show that the proposed scheme, referred to as SegOMP, yields higher probability of exact recovery in theory. It is finished with much smaller number of measurements to achieve a same reconstruction quality when compared to the canonical greedy algorithms. Extensive experiments verify the validity of the SegOMP and demonstrate its potentials.

Tracking capsule endoscope location is one of the promising applications offered by implant body area networks (BANs). When tracking the capsule endoscope location, i.e., continuously localize it, it is effective to take the weighted sum of its past locations to its present location, in other words, to low-pass filter its past locations. Furthermore, creating an exact mathematical model of location transition will improve tracking performance. Therefore, in this paper, we investigate two tracking methods with received signal strength indicator (RSSI)-based localization in order to solve the capsule endoscope location tracking problem. One of the two tracking methods is finite impulse response (FIR) filter-based tracking, which tracks the capsule endoscope location by averaging its past locations. The other one is particle filter-based tracking in order to deal with a nonlinear transition model on the capsule endoscope. However, the particle filter requires that the particle weight is calculated according to its condition (namely, its likelihood value), while the transition model on capsule endoscope location has some model parameters which cannot be estimated from the received wireless signal. Therefore, for the purpose of applying the particle filter to capsule endoscope tracking, this paper makes some modifications in the resampling step of the particle filter algorithm. Our computer simulation results demonstrate that the two tracking methods can improve the performance as compared with the conventional maximum likelihood (ML) localization. Furthermore, we confirm that the particle filter-based tracking outperforms the conventional FIR filter-based tracking by taking the realistic capsule endoscope transition model into consideration.

Attenuated and delayed versions of the pulse signal overlap in multipath propagation. Previous algorithms can resolve them only if signal sampling is ideal, but fail to resolve two counterparts with non-ideal sampling. In this paper, we propose a novel method which can resolve the general types of non-ideally sampled pulse signals in the time domain via Taylor Series Expansion (TSE) and estimate multipath signals' precise time delays and amplitudes. In combination with the CLEAN algorithm, the overlapped pulse signal parameters are estimated one by one through an iteration method. Simulation results verify the effectiveness of the proposed method.

In recent VLSIs, small-delay defects, which are hard to detect by traditional delay fault testing, can bring about serious issues such as short lifetime. To detect small-delay defects, on-chip delay measurement which measures the delay time of paths in the circuit under test (CUT) was proposed. However, this approach incurs high test cost because it uses scan design, which brings about long test application time due to scan shift operation. Our solution is a test application time reduction method for testing using the on-chip path delay measurement. The testing with on-chip path delay measurement does not require capture operations, unlike the conventional delay testing. Specifically, FFs keep the transition pattern of the test pattern pair sensitizing a path under measurement (PUM) (denoted as p) even after the measurement of p. The proposed method uses this characteristic. The proposed method reduces scan shift time and test data volume using test pattern merging. Evaluation results on ISCAS89 benchmark circuits indicate that the proposed method reduces the test application time by 6.89∼62.67% and test data volume by 46.39∼74.86%.

In this paper, we propose a bitstream-level noise cancellation method for playback applications of damaged video. Most analog video data such as movies, news and historical research videos are now stored in a digital format after a series of conversion processes that include analog-to-digital conversion and compression. In many cases, noise such as blotches and line scratching remaining in analog media are not removed during the conversion process. On the other hand, noise is propagated in the compression stage because most media compression technologies use predictive coding. Therefore, it is imperative to efficiently remove or reduce the artifacts caused by noise as much as possible. In some cases, the video data with historical values are to be preserved without correcting the noise in order not to lose any important information resulting from the noise removal process. However, playback applications of such video data still need to undergo a noise reduction process to ensure picture quality for public viewing. The proposed algorithm identifies the candidate noise blocks at the bitstream-level to directly provide a noise reduction process while decoding the bitstream. Throughout the experimental results, we confirm the efficiency of the proposed method by showing RR and PR values of around 70 percent.

In this letter, we research the method of using face and gesture image sequences to deal with the video-based bimodal emotion recognition problem, in which both Harris plus cuboids spatio-temporal feature (HST) and sparse canonical correlation analysis (SCCA) fusion method are applied to this end. To efficaciously pick up the spatio-temporal features, we adopt the Harris 3D feature detector proposed by Laptev and Lindeberg to find the points from both face and gesture videos, and then apply the cuboids feature descriptor to extract the facial expression and gesture emotion features [1],[2]. To further extract the common emotion features from both facial expression feature set and gesture feature set, the SCCA method is applied and the extracted emotion features are used for the biomodal emotion classification, where the K-nearest neighbor classifier and the SVM classifier are respectively used for this purpose. We test this method on the biomodal face and body gesture (FABO) database and the experimental results demonstrate the better recognition accuracy compared with other methods.

The exact power distribution of the inter-cell interference is obtained explicitly for cell edge users who are surrounded by circular guard zones. Compared with recent works, the underlying channel model is generalized from Rayleigh fading to a combination of Nakagami fading and Gamma shadowing. In addtion, asymptotic analysis shows that the mean power of intercell interference changes from infinite to finite with a guard zone. Based on this interference distribution, the average capacity at the cell edge is further obtained. Special case approximation indicates that the capacity scales proportionally to the exponential of the guard zone size. Analytical capacities are validated by Monte Carlo simulations.

This letter proposes a noise spectrum estimation algorithm for speech enhancement. The algorithm incorporates the speech presence probability, which is calculated from SNR (signal-to-noise ratio) discrepancy. The discrepancy is measured based on the estimation of the a priori and a posteriori SNR. The proposed algorithm is found to be effective in rapidly switched noise environments. This is confirmed by the experimental results which indicate that the proposed algorithm when integrated in a speech enhancement scheme performs better than conventional noise estimation algorithms.

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Image binarization refers to convert gray-level images into binary ones, and many binarization algorithms have been developed. The related algorithms can be classified as either high quality computation or high speed performance. This letter presents an algorithm that ensures both benefits at the same time. The proposed algorithm intelligently segments input images into several sub-image, after which the sub-image binarization is performed independently. Experimental results reveal that our algorithm provides the appropriate quality with the medium speed.

We investigated the filling-in (FI) of line segments at the Artificial Scotoma (AS) created by Motion Induced Blindness (MIB). The FI sensations for line segments were fairly similar to that of the natural Blind Spots (BS), though the geometrical configurations and luminance conditions on stimuli were substantially limited. The 2.5 degree thick black line segment was filled in after 6.5 degree diameter disk was disappeared by MIB. The thin lines, however, didn't fill in. We also obtained the pro and con evidences for the historical FI theory. The disappearance of the uniformly filled circles followed the general FI theory. On the other hand we found it controversial with the FI accounts that the concentric circles disappeared altogether. In the conventional MIB, the target figure disappears and re-appears in a stochastic and spontaneous manner. We devised the novel inducer for MIB so as to yield the synchronization of dis- and re-appearance of the targets with the motion of the inducers. The two stationary disks disappeared in an alternating manner by MIB effects. The subjects observed the background color after disappearance. The alternating disappearance of the two white disks provided the observers with the sensation of the Apparent Motion (AM) of the single disk which would be perceived as jumping up and down. The significant question was raised; did MIB precede AM? When the AM sensation was the case, the percept was not the disappearance but the motion of the single entity. The sensation of the motion provided the almost equivalent conditions to the motion stimuli over the natural BS. We summarized the issue whether the FI at AS by MIB was intrinsically equivalent to the phenomena on BS. The hierarchy of underlying mechanisms of AM and MIB was yet unknown, however, we rather proposed yet another high level motion perception mechanism.

Packet loss and energy dissipation are two major challenges of designing large-scale wireless sensor networks. Since sensing data is spatially correlated, compressed sensing (CS) is a promising reconstruction scheme to provide low-cost packet error correction and load balancing. In this letter, assuming a multi-hop network topology, we present a CS-oriented data aggregation scheme with a new measurement matrix which balances energy consumption of the nodes and allows for recovery of lost packets at fusion center without additional transmissions. Comparisons with existing methods show that the proposed scheme offers higher recovery precision and less energy consumption on TinyOS.

The fading channel model is seen as an important approach that can efficiently capture the basic time-varying properties of wireless channels, while physical layer security is a promising approach to providing a strong form of security. This paper focuses on the fundamental performance study of applying physical layer security to achieve secure and reliable information transmission over the fading wire-tap channel. For the practical scenario where the main channel is correlated with the eavesdropper channel but only the real time channel state information (CSI) of the main channel is known at the transmitter, we conduct a comprehensive study on the fundamental performance limits of this system by theoretically modeling its secrecy capacity, transmission outage probability and secrecy outage probability. With the help of these theoretical models, we then explore the inherent performance tradeoffs under fading wire-tap channel and also the potential impact of channel correlation on such tradeoffs.

In cognitive radio systems using TV white space, it is desirable to secure a control channel to exchange the wireless network control information and to secure minimum frequency resource for secondary user communications if TV white space is unavailable. In order to satisfy these requirements, this paper proposes guard band utilization, which aggregates the multiple guard bands between digital TV signals and uses them for a control channel and/or a communication channel. To investigate the feasibility of the proposed scheme, this paper evaluates the performance degradation of the digital TV signals when the guard band is used. Furthermore, it discusses the permissible transmitting power and occupied bandwidth of the guard band signals to avoid the harmful interference to the digital TV signals.

We propose a 2 × 2 space-time block code based on a trace criterion for 64-quadrature amplitude modulation (QAM). We introduce a method to easily calculate the trace norm of a space-time code for 64-QAM, and propose a new space-time code searched by this method. The error rate performance of the proposed code is compared with that of the Alamouti code. By comparison of the theoretical upper bounds, the proposed space-time code is better than the Alamouti code, when the number of receiving antennas is more than one. Moreover, bit error rate performance of the proposed code is compared with maximum likelihood decoding on perfect channel state information Rayleigh fading channels by computer simulations. These results show the proposed code almost outperforms the Alamouti code when the number of receive antennas is more than one, and the increased number of receiving antennas with our code is a decided advantage.

This paper introduces a comparison of three automatic gait generation methods for quadruped robots: GA (Genetic Algorithm), GP (genetic programming) and CPG (Central Pattern Generator). It aims to provide a useful guideline for the selection of gait generation methods. GA-based approaches seek to optimize paw locus in Cartesian space. GP-based techniques generate joint trajectories using regression polynomials. The CPGs are neural circuits that generate oscillatory output from an input coming from the brain. Optimizations for the three proposed methods are executed and analyzed using a Webots simulation of the quadruped robot built by Bioloid. The experimental comparisons and analyses provided herein will be an informative guidance for research of gait generation method.

A fast and accurate architecture exploration for high performance and low energy VLIW data-path is proposed. The main contribution is a method to find Pareto optimal FU structures, i.e., the optimal number of FUs and the best instruction assignment for each FU. The proposed architecture exploration method is based on GA and enables the effective exploration of vast solution space. Experimental results showed that proposed method was able to achieve fast and accurate architecture exploration. For most cases, the estimation error was less than 1%.

Cyclic codes are a subclass of linear codes and have applications in consumer electronics, data storage systems, and communication systems as they have efficient encoding and decoding algorithms compared with the linear block codes. The objective of this letter is to present a new family of ternary cyclic codes with parameters [3m-1,3m-1-2m,4], where m is an odd integer. The proposed cyclic codes are optimal in the sense that their parameters meet the Sphere Packing bound.

We analyze the effect of the propagation of route request packets in ad hoc network routing protocols such as DSR and AODV. So far it has not been clear how the number density of route request packets depends on propagation and hop counts. By stochastic analysis, it is found that the collisions of route request packets can be avoided efficiently by adjusting the number of the relevant nodes in the early stages of propagation.

The sparse matrix operation, y ← y+AtAx, where A is a sparse matrix and x and y are dense vectors, is a widely used computing pattern in High Performance Computing (HPC) applications. The pattern poses challenge to efficient solutions because both a matrix and its transposed version are involved. An efficient sparse matrix format, Compressed Sparse Blocks (CSB), has been proposed to provide nearly the same performance for both Ax and Atx. We develop a multithreaded implementation for the CSB format and apply it to solve y ← y+AtAx. Experiments show that our technique outperforms the Compressed Sparse Row (CSR) based solution in POSKI by up to 2.5 fold on over 70% of benchmarking matrices.