The application of nonlinear structures to the reconstruction ofbinary signals

The problem of reconstructing digital signals which have been passed through a dispersive channel and corrupted with additive noise is discussed. The problems encountered by linear equalizers under adverse conditions on the signal-to-noise ratio and channel phase are described. By considering the equalization problem as a geometric classification problem the authors demonstrate how these difficulties can be overcome by utilizing nonlinear classifiers as channel equalizers. The manner in which neural networks can be utilized as adaptive channel equalizers is described, and simulation results which suggest that the neural network equalizers offer a performance which exceeds that of the linear structures, particularly in the high-noise environment, are presented     

Off-state drain breakdown mechanisms of VDMOS with anti-JFET implantation

Efficiency, reliability, and cost are the important design considerations of a vertical double diffused MOSFET (VDMOS) because of its high-voltage applications in consumer electronics. To minimize the cost, the devices were normally fabricated on an epitaxial layer which was grown on a highly-doped substrate. Meanwhile, it was proposed that the efficiency of a VDMOS can be enhanced by conducting an anti-JFET implant to reduce the “ON” resistance of the transistor. This paper reports the effects of anti-JFET implant on the reliability and the blocking capability of the VDMOS. Experimental results show that the anti-JFET implant can reduce the ON resistance by suppressing the channel depletion due to the parasitic JFET and enhance the breakdown voltage by moving the high-field region to the surface channel region. However, it deteriorates the device reliability greatly because the oxide quality was deteriorated and the hot holes generated in the surface high-field region could be easily injected into the gate oxide and hence caused larger subthreshold conduction and drain breakdown at lower voltage.     

Adaptive joint beamforming and B‐MMSE detection for CDMA signal reception under multipath interference

The combination of antenna array beamforming with multiuser detection can effectively improve the detection efficiency of a wireless system under multipath interference, especially in a fast‐fading channel. This paper studies the performance of an adaptive beamformer incorporated with a block‐wise minimum mean square error(B‐MMSE) detector, which works on a unique signal frame characterized by training sequence preamble and data blocks segmented by zero‐bits. Both beam‐former weights updating and B‐MMSE detection are carried out by either least mean square (LMS) or recursive least square (RLS) algorithm. The comparison of the two adaptive algorithms applied to both beamformer and B‐MMSE detector will be made in terms of convergence behaviour and estimation mean square error. Various multipath patterns are considered to test the receiver's responding rapidity to changing multipath interference. The performance of the adaptive B‐MMSE detector is also compared with that of non‐adaptive version (i.e. through direct matrix inversion). The final performance in error probability simulation reveals that the RLS/B‐MMSE scheme outperforms non‐adaptive B‐MMSE by 1–5 dB, depending on the multipath channel delay profiles of concern. The obtained results also suggest that adaptive beamformer should use RLS algorithm for its fast and robust convergence property; while the B‐MMSE filter can choose either LMS or RLS algorithm depending on antenna array size, multipath severity and implementation complexity. Copyright © 2004 John Wiley & Sons, Ltd.     

基于HBP编码结构的MVC快速算法

针对MVC系统中运算量最大的矢量预测部分——单向搜索和双向搜索,该文提出一种快速算法。根据多视点视频的序列相关性,采用立体-运动约束模型在运动域和视差域进行联合迭代单向搜索,设计可信度因子来自适应地调整修正搜索窗口,同步搜索得到运动和视差矢量。此外,通过分析双向预测宏块的特性,提出一种双向搜索提前中止算法。实验结果证明该文算法的有效性,能在保持编码质量的同时极大减少算法复杂度。     

An efficient search strategy for block motion estimation usingimage features

Block motion estimation using the exhaustive full search is computationally intensive. Fast search algorithms offered in the past tend to reduce the amount of computation by limiting the number of locations to be searched. Nearly all of these algorithms rely on this assumption: the mean absolute difference (MAD) distortion function increases monotonically as the search location moves away from the global minimum. Essentially, this assumption requires that the MAD error surface be unimodal over the search window. Unfortunately, this is usually not true in real-world video signals. However, we can reasonably assume that it is monotonic in a small neighborhood around the global minimum. Consequently, one simple strategy, but perhaps the most efficient and reliable, is to place the checking point as close as possible to the global minimum. In this paper, some image features are suggested to locate the initial search points. Such a guided scheme is based on the location of certain feature points. After applying a feature detecting process to each frame to extract a set of feature points as matching primitives, we have extensively studied the statistical behavior of these matching primitives, and found that they are highly correlated with the MAD error surface of real-world motion vectors. These correlation characteristics are extremely useful for fast search algorithms. The results are robust and the implementation could be very efficient. A beautiful point of our approach is that the proposed search algorithm can work together with other block motion estimation algorithms. Results of our experiment on applying the present approach to the block-based gradient descent search algorithm (BBGDS), the diamond search algorithm (DS) and our previously proposed edge-oriented block motion estimation show that the proposed search strategy is able to strengthen these searching algorithms. As compared to the conventional approach, the new algorithm, through the extraction of image features, is more robust, produces smaller motion compensation errors, and has a simple computational complexity.     

Locating the eye in human face images using fractal dimensions

Facial feature extraction is an important step in many applications such as human face recognition, video conferencing, surveillance systems, human computer interfacing etc. The eye is the most important facial feature. A reliable and fast method for locating the eye pairs in an image is vital to many practical applications. A new method for locating eye pairs based on valley field detection and measurement of fractal dimensions is proposed. Possible eye candidates in an image with a complex background are identified by valley field detection. The eye candidates are then grouped to form eye pairs if their local properties for eyes are satisfied. Two eyes are matched if they have similar roughness and orientation as represented by fractal dimensions. A modified approach to estimating fractal dimensions that is less sensitive to lighting conditions and provides information about the orientation of an image under consideration is proposed. Possible eye pairs are further verified by comparing the fractal dimensions of the eye-pair window and the corresponding face region with the respective means of the fractal dimensions of the eye-pair windows and the face regions. The means of the fractal dimensions are obtained based on a number of facial images in a database. Experiments have shown that this approach is fast and reliable     

A fast and effective model for wavelet subband histograms and its application in texture image retrieval.

This paper presents a novel, effective, and efficient characterization of wavelet subbands by bit-plane extractions. Each bit plane is associated with a probability that represents the frequency of 1-bit occurrence, and the concatenation of all the bit-plane probabilities forms our new image signature. Such a signature can be extracted directly from the code-block code-stream, rather than from the de-quantized wavelet coefficients, making our method particularly adaptable for image retrieval in the compression domain such as JPEG2000 format images. Our signatures have smaller storage requirement and lower computational complexity, and yet, experimental results on texture image retrieval show that our proposed signatures are much more cost effective to current state-of-the-art methods including the generalized Gaussian density signatures and histogram signatures.     

Influence of multi-finger layout on the subthreshold behavior of nanometer MOS transistors

This work studies the effects of number of gate finger on the DC subthreshold characteristics of multi-finger nanoscale MOS transistors. We found in not optimally-tempered nanoscale (gate length = 90 nm) MOS transistors that the significantly deteriorated subthreshold characteristics can be effectively improved by increasing the number of gate finger. This observation was explained with a modified subthreshold slope model based on voltage-doping transformation theory. Hence, the multi-finger structure does not only enhance the operation frequency, it also improves the subthreshold DC characteristics of the nanoscale MOS transistors.     

Degradation behaviors of GaN light-emitting diodes under high-temperature and high-current stressing

A number of commercially available multiple-quantum well (MQW) InGaN/GaN blue LEDs with wavelengths of about 460 nm and a power of 1 mW were stressed at temperatures ranging from 25 to 120 °C at several accelerated DC currents. Both the forward and reverse current voltage characteristics as well as the electroluminescent spectra of the LEDs were monitored. These effects also resulted in the pronounced degradation of light efficiency and device operation lifetime. We found that the degradation of photonic characteristics, correlated very well with the generation-recombination current which is governed by the defect density. The device degradation is much faster at high temperatures. At nominal operation current and at room temperature, the light intensity degradation reaches a saturation level before the light dyes out. These results shed new lights upon the design and lifetime specifications for the emerging commercial solid-state lighting devices.     

Preliminary Characterization of Novel Extra-cellular Lipase from Penicillium crustosum Under Solid-State Fermentation and its Potential Application for Triglycerides Hydrolysis

Current studies about lipase production involve the use of agro-industrial residues and newly isolated microorganisms aimed at increasing economic attractiveness of the process. Based on these aspects, the main objective of this work is to perform the partial characterization of enzymatic extracts produced by a newly isolated Penicillium crustosum in solid-state fermentation. Lipase extract presented optimal temperature and pH of 37?°C and 9?C10, respectively. The concentrated enzymatic extract showed more stability at 25?°C and pH?7. The enzymes kept 100% of their enzymatic activity until 60?days of storage at 4 and ?10?°C. The stability under calcium salts indicated that the hydrolytic activity presented decay with the increase of calcium concentration. The specificity under several substrates indicated good enzyme activities in triglycerides from C4 to C18.