Implementation of RNS-Based Distributed Arithmetic Discrete Wavelet Transform Architectures Using Field-Programmable Logic

Currently there are design barriers inhibiting the implementation of high-precision digital signal processing (DSP) objects with field programmable logic (FPL) devices. This paper explores overcoming these barriers by fusing together the popular distributed arithmetic (DA) method with the residue number system (RNS) for use in FPL-centric designs. The new design paradigm is studied in the context of a high-performance filter bank and a discrete wavelet transform (DWT). The proposed design paradigm is facilitated by a new RNS accumulator structure based on a carry save adder (CSA). The reported methodology also introduces a polyphase filter structure that results in a reduced look-up table (LUT) budget. The 2C-DA and RNS-DA are compared, in the context of a FPL implementation strategy, using a discrete wavelet transform (DWT) filter bank as a common design theme. The results show that the RNS-DA, compared to a traditional 2C-DA design, enjoys a performance advantage that increases with precision (wordlength).     

无纵向电场分量离子波纹激光的小信号增益

在离子波纹摆动器中，改变电子束的入射方向，保证了离子波纹场的纵向分量为零，从而消除了纵向电场对离子波纹激光的不利影响。给出了束电子的运动轨迹，运用Madey定理计算了小振幅条件下该离子波纹激光的小信号增益。     

基于多抽样率信号处理的无源雷达MTD方法

以数字电视信号为机会照射源的雷达系统研究为背景 ,提出用以多抽样率信号处理为基础的多级抽取信号处理算法解决运动目标检测中海量数据处理问题。文中叙述了数字电视广播信号回波的数学模型、多级抽取基本原理、目标检测算法 ,以数字电视信号为反射回波做了仿真 ,对运动目标进行检测 ,并对仿真结果做了分析。     

Study on the Complexity of the Bullwhip Effect

Recent years have witnessed a rapid growth of interest in the study of the dynamic behavior of replenishment rules of bullwhip effect. We prove that bullwhip effect and butterfly effect share a same the self-oscillation amplifying mechanism that is the ordering decisions the supplier self-oscillation amplify the perturbations brought by the errors in the processing of retailers' demand information. This results as an explicit self-similar structure of the sensitivity of the system to the initial values duty to the nonlinear mechanism. In this paper, the causes process of the bullwhip effect is described as the internal nonlinear mechanism and study on the complexity of bullwhip effect for order-up-to policy under demand signal processing. The methodology is based on fractal and chaotic theory and allows important insights to be gained about the complexity behavior of bullwhip effect.     

基于AT89C2051的单户可视对讲门铃室内分机的设计

本文介绍一种基于单片机AT89C2501的单户可视对讲门铃室内分机的工作原理及软、硬件的设计与实现方法。     

基于WVD的防空雷达直升机信号特征分析

基于直升机目标旋转部件的调制模型，本文针对防空雷达提出了分析直升机信号特征的一种新方法——WVD法，并对直升机目标旋转部件调制回波信号在不同噪声情况下加以仿真分析，结果表明：用WVD分析雷达回波中直升机信号特征是一种非常有效的方法。     

Signal Integrity: Fault Modeling and Testing in High-Speed SoCs

As we approach 100 nm technology the interconnect issues are becoming one of the main concerns in the testing of gigahertz system-on-chips. Voltage distortion (noise) and delay violations (skew) contribute to the signal integrity loss and ultimately functional error, performance degradation and reliability problems. In this paper, we first define a model for integrity faults on the high-speed interconnects. Then, we present a BIST-based test methodology that includes two special cells to detect and measure noise and skew occurring on the interconnects of the gigahertz system-on-chips. Using an inexpensive test architecture the integrity information accumulated by these special cells can be scanned out for final test and reliability analysis.     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

子波变换理论及其在信号处理中的应用

子波分析的形成是傅里叶分析发展史上里程碑式的进展，子波分析优于傅里叶交换的地方在于它在时域和频域同时具有良好的局部化性质，从而可以把分析的重点聚焦到任意的细节，被人们誉为数学显微镜，成为近年来在工具和方法上的重大突破。本文将子波理论中的主要定理、结论、变换特性和一些重要概念加以综述，以促进子波理论的应用。本文的重点在于介绍多分辨率分析和子波分析及其实现、子波变换及其算法、子波和滤波器组等的重要内容，并介绍其在信号处理中的应用及研究动态。     

模拟信号的恢复及其误差研究

数模混合仿真中模拟信号的恢复及其误差对整个仿真过程具有重要影响。本文探讨了用零阶保持和一阶保持进行信号恢复的方法，比较了它们的误差及工作特点。特别指出了一阶保持中，由于存在积分器复原时间及数字机操作时间的影响而会带来附加的误差，因此一阶保持方法较难达到其理论的精度。