This paper describes on-line recognition of handwritten Lao characters by adopting Markov random field (MRF). The character set to recognize includes consonants, vowels and tone marks, 52 characters in total. It extracts feature points along the pen-tip trace from pen-down to pen-up, and then sets each feature point from an input pattern as a site and each state from a character class as a label. It recognizes an input pattern by using a linear-chain MRF model to assign labels to the sites of the input pattern. It employs the coordinates of feature points as unary features and the transitions of the coordinates between the neighboring feature points as binary features. An evaluation on the Lao character pattern database demonstrates the robustness of our proposed method with recognition rate of 92.41% and respectable recognition time of less than a second per character.

The scattering from a phase change disk that is illuminated by an optical near field through a ridged-square nano-aperture was analyzed. A finite-difference time-domain (FDTD) method installed with motion equations of free electrons was used in the analysis and a three dimensional disk structure was taken into consideration. The far-field scattering patterns from the phase change disk were analyzed and the sum-signal output through a condenser lens was calculated. The crosstalk between plural marks and the readout characteristics of mark trains were investigated.

This paper proposes a write resistance tracking circuit (WRTC) to improve the memory window of HfOx-based resistive memory. With a 50-ns single voltage pulse, the minimal resistance of the high resistance state in the 1-kb array of resistive switching elements can increase from 25 kΩ to 65 kΩ by using the proposed verify circuit. The WRTC uses the transition current detection method based on the feedback of the memory cell to control the write driver. The WRTC achieves distinct bistable resistance states, avoids the occurrence of over-RESET, and enhances the memory window of the RRAM cell.

This paper deals with an integral method analyzing the diffraction of a transverse electric (TE) wave by a perfectly conductive periodic surface. The conventional integral method fails to work for a critical angle of incidence. To overcome such a drawback, this paper applies the method of image Green's function. We newly obtain an image integral equation for the basic surface current in the TE case. The integral equation is solved numerically for a very rough sinusoidal surface. Then, it is found that a reliable solution can be obtained for any real angle of incidence including a critical angle.

Mel Frequency Cepstral Coefficients (MFCC) are the most popular acoustic features used in automatic speech recognition (ASR), mainly because the coefficients capture the most useful information of the speech and fit well with the assumptions used in hidden Markov models. As is well known, MFCCs already employ several principles which have known counterparts in the peripheral properties of human hearing: decoupling across frequency, mel-warping of the frequency axis, log-compression of energy, etc. It is natural to introduce more mechanisms in the auditory periphery to improve the noise robustness of MFCC. In this paper, a k-nearest neighbors based frequency masking filter is proposed to reduce the audibility of spectra valleys which are sensitive to noise. Besides, Moore and Glasberg's critical band equivalent rectangular bandwidth (ERB) expression is utilized to determine the filter bandwidth. Furthermore, a new bandpass infinite impulse response (IIR) filter is proposed to imitate the temporal masking phenomenon of the human auditory system. These three auditory perceptual mechanisms are combined with the standard MFCC algorithm in order to investigate their effects on ASR performance, and a revised MFCC extraction scheme is presented. Recognition performances with the standard MFCC, RASTA perceptual linear prediction (RASTA-PLP) and the proposed feature extraction scheme are evaluated on a medium-vocabulary isolated-word recognition task and a more complex large vocabulary continuous speech recognition (LVCSR) task. Experimental results show that consistent robustness against background noise is achieved on these two tasks, and the proposed method outperforms both the standard MFCC and RASTA-PLP.

Classical jamming attack models in the time domain have been proposed, such as constant jammer, random jammer, and reactive jammer. In this letter, we consider a new problem: given k jammers, how does the attacker minimize the pair-wise connectivity among the nodes in a Wireless Sensor Network (WSN)? We call this problem k-Jammer Deployment Problem (k-JDP). To the best of our knowledge, this is the first attempt at considering the position-critical jamming attack against wireless sensor network. We mainly make three contributions. First, we prove that the decision version of k-JDP is NP-complete even in the ideal situation where the attacker has full knowledge of the topology information of sensor network. Second, we propose a mathematical formulation based on Integer Programming (IP) model which yields an optimal solution. Third, we present a heuristic algorithm HAJDP, and compare it with the IP model. Numerical results show that our heuristic algorithm is computationally efficient.

Topology control is one of the key issues in wireless networks. In this letter, we propose a simple topology control algorithm based on Connected Dominant Set (CDS) theory. The proposed algorithm uses less memory and less overhead cost than other existing schemes, and is therefore appropriate for implementation in wireless sensor networks. We will prove that the algorithm can form a CDS and guarantee network connectivity. The performance of our algorithm is demonstrated by simulation results.

A 4th-order programmable continuous-time filter (CTF) for hard-disk-drive (HDD) read channels was developed with 65-nm CMOS process technology. The CTF cutoff frequency and boost are programmable by switching units of the operational trans-conductance amplifier (OTA) banks and the capacitor banks. The switches are operated by lifted local-supply voltage to reduce on-resistance of the transistors. The CTF characteristics were robust against process technology variations and supply voltage and temperature ranges due to the introduction of a digitally assisted compensation scheme with analog auto-tuning circuits and digital calibration sequences. The digital calibration sequences, which fit into the operation sequence of the HDD read channel, compensate for the tuning circuits of the process technology variations, and the tuning circuits compensate for the CTF characteristics over the supply voltage and temperature ranges. As a result, the CTF had a programmability of 100–1000-MHz cutoff frequency and 0–12-dB boost.

This paper investigates the non-data-aided (NDA) carrier frequency estimation of amplitude and phase shift keying (APSK) signals. The true Cramer-Rao bound (CRB) for NDA frequency estimation of APSK signals are derived and evaluated numerically. Characteristic and jitter variance of NDA Luise and Reggiannini (L&R) frequency estimator are analyzed. Verified by Monte Carlo simulations, the analytical results are shown to be accurate for medium-to-high signal-to-noise ratio (SNR) values. Using the proposed closed-form expression, parameters of the algorithm are optimized efficiently to minimize the jitter variance.

In this letter, we address the performance analysis of underlay selective decode-and-forward (DF) relay networks in Rayleigh fading channels with non-necessarily identical fading parameters. In particular, a novel result on the outage probability of the considered system is presented. Monte Carlo simulations are performed to verify the correctness of our exact closed-form expression. Our proposed analysis can be adopted for various underlay spectrum sharing applications of cognitive DF relay networks.

To improve the robustness and transparency of spread spectrum (SS) based watermarking, this paper presents a new informed embedding strategy, which we call selective host-interference cancellation. We show that part of the host-interference in SS-based watermarking is beneficial to blind watermark extraction or detection, and can be utilized rather than removed. Utilizing this positive effect of the host itself can improve the watermark robustness without significantly sacrificing the media fidelity. The proposed strategy is realized by selectively applying improved SS (ISS) modulation to traditional SS watermarking. Theoretically, the error probability of the new method under additive white Gaussian noise attacks is several orders of magnitude lower than that of ISS for high signal-to-watermark ratios, and the required minimum watermark power is reduced by 3dB. Experiments were conducted on real audio signals, and the results show that our scheme is robust against most of common attacks even in high-transparency or high-payload applications.

Joint transmit and receive antenna selection (JTRAS) is proposed for the multiple-input multiple-output (MIMO) two-way relaying channel. A simple and closed-form lower bound on the outage probability of JTRAS is derived. Furthermore, asymptotic analysis reveals that JTRAS can attain the maximum achievable diversity order of the MIMO dual-hop relaying channel.

This paper presents a new type of electromagnetic interference (EMI) measurement system. An EMI Camera LSI (EMcam) with a 124 on-chip 25050 µm2 loop antenna matrix in 65 nm CMOS is developed. EMcam achieves both the 2D electric scanning and 60 µm-level spatial precision. The down-conversion architecture increases the bandwidth of EMcam and enables the measurement of EMI spectrum up to 3.3 GHz. The shared IF-block scheme is proposed to relax both the increase of power and area penalty, which are inherent issues of the matrix measurement. The power and the area are reduced by 74% and 73%, respectively. EMI measurement with the smallest 3212 µm2 antenna to date is also demonstrated.

Lazy-task creation is an efficient method of overcoming the overhead of the grain-size problem in parallel computing. Work stealing is an effective load balancing strategy for parallel computing. In this paper, we present dynamic work stealing strategies in a lazy-task creation technique for efficient fine-grain task scheduling. The basic idea is to control load balancing granularity depending on the number of task parents in a stack. The dynamic-length strategy of work stealing uses run-time information, which is information on the load of the victim, to determine the number of tasks that a thief is allowed to steal. We compare it with the bottommost first work stealing strategy used in StackThread/MP, and the fixed-length strategy of work stealing, where a thief requests to steal a fixed number of tasks, as well as other multithreaded frameworks such as Cilk and OpenMP task implementations. The experiments show that the dynamic-length strategy of work stealing performs well in irregular workloads such as in UTS benchmarks, as well as in regular workloads such as Fibonacci, Strassen's matrix multiplication, FFT, and Sparse-LU factorization. The dynamic-length strategy works better than the fixed-length strategy because it is more flexible than the latter; this strategy can avoid load imbalance due to overstealing.

In this letter, we describe a low power current to time converter for wireless sensor networks. The proposed circuit has some advantages of high linearity and wide measurement range. From the evaluation using HSPICE with 0.18 µm CMOS device parameters, the output differential error for the input current variation is approximately 0.1 µs/nA under the condition that the current is varied from 100 nA to 500 nA. The idle power consumption is approximately zero.

This paper proposes a method of accurately detecting the boundary of narrow stripes, such as lane markings, by employing gradient cues of edge points. Using gradient direction cues, the edge points at the two sides of the boundary of stripes are classified into two groups before the Hough transform is applied to extract the boundary lines. The experiments show that the proposed method improves significantly the performance in terms of the accuracy of boundary detection of narrow stripes over the conventional approaches without edge point grouping.

The lateral velocity is of importance in cases like target identification and traffic management. Conventional Doppler methods are not capable of measuring lateral velocities since they quantify only the radial component. Based on the spectrogram characteristic of laterally moving targets, an algorithm based on fractional Fourier transform has been studied in the signal processing literature. The algorithm searches the peak position of the transformation, and calculates the lateral velocity from the peak position. The performance analysis of this algorithm is carried out in this paper, which shows that this algorithm approaches Cramer-Rao bound with reasonable computational complexity. Simulations are conducted at last to compare the analytical performance and the experimental result.

This letter summarizes three talks in the tutorial session of the 13th Asia-Pacific Network Operations and Management Symposium (APNOMS2011), which focused on the disaster recovery and further emergency management regarding the Great East Japan Earthquake of 2011. We present the damage and restoration of communication networks and points to a future disaster-resilient society.

An amplitude-redistribution technique – which improves phase-noise performance of millimeter (mm)-wave and quasi mm-wave cross-coupled VCOs by controlling the distribution of voltage swings on the oscillator nodes – is proposed. A 28-GHz VCO, fabricated in 0.13-µm CMOS technology, uses this technique and demonstrates low phase-noise performance of -112.9-dBc/Hz at 1-MHz offset and FOMT of -187.4-dBc/Hz, which is the highest FOMT so far reported in regard to CMOS VCOs operating above 25 GHz.

The mining of a complete set of frequent subgraphs from labeled graph data has been studied extensively. Furthermore, much attention has recently been paid to frequent pattern mining from graph sequences (dynamic graphs or evolving graphs). In this paper, we define a novel subgraph subsequence class called an “induced subgraph subsequence” to enable the efficient mining of a complete set of frequent patterns from graph sequences containing large graphs and long sequences. We also propose an efficient method for mining frequent patterns, called “FRISSs (Frequent Relevant, and Induced Subgraph Subsequences)”, from graph sequences. The fundamental performance of the method is evaluated using artificial datasets, and its practicality is confirmed through experiments using a real-world dataset.