小波变换在光谱特征提取方面的应用

人们在处理高光谱图像时一般要对一些典型地物进行光谱分析、特征波段的提取,以便提取出最大量的有效信息,剔除无用或冗余的信息,然后再进行分类识别.采用小波变换的分析方法,选用合适的小波进行分解,根据分解后的高频分量中包含的重要信息,利用局部相邻的正负极值点找出对应于原始光谱曲线上每个吸收带的左右边界;利用局部过零点,即可比较精确的提取出各个吸收带的中心波长.该方法比传统的光谱特征提取方法更简洁、有效,实验证明为一种比较理想的光谱特征提取方法.     

提取地震信号高频信息方法的若干问题

岩性油气藏勘探已成为当代油气勘探的重要组成部分,因此提取地震资料高频信息已成为一个重要研究课题。文中对分辨率、分频处理地震信号、波阻抗反演中的一些问题进行了较深入的讨论,并得出以下认识:1要提高垂向和横向分辨率,必须设法提高野外采集地震资料的频率;2地震分频处理是偏移后提高分辨率的常用方法之一,这种方法应该限定在地震波的有效频带内,而超出有效频带,可能会带来很多假像;3低频合成地震记录中高频反射系数存在不确定性。在基于模型波阻抗反演的方法中,反演结果受初始模型的影响非常大,初始模型是依据测井资料建立的,初始模型与实际情况越接近,反演效果就越好;否则,会产生模型化的现象;4在相对波阻抗数据体(相当于地震数据体)作为约束条件下的SP测井参数协克里金插值是正演过程,消除了模型化的问题,使反演结果更接近真实情况,提高了砂层真实的分辨率。     

地震平衡技术及其在地震反演中的应用

地震平衡技术是一种在地震反演中改善井震关系的新技术。它通过单井对比、空间分形建模以及平衡处理的手段 ,克服地震反演中子波空变的影响 ,使得经过地震平衡技术处理的地震剖面井震关系得到较好改善 ,从而可以用统一的子波对研究区的地震资料进行反演     

电力系统谐波检测的现状与发展

准确、实时地对电力系统谐波进行检测有着重要的意义。本文根据电力系统谐波测量的基本方法，对近年来电力系统谐波检测的新方法进行了分析和评述。最后对电力系统的谐波测量进行了总结并提出了看法。     

Quality Control for Scalable Media Processing Applications

Many media processing applications create a load that varies significantly over time. Hence, if such an application is assigned a lower processing-time budget than needed in its worst-case load situation, deadline misses are likely to occur. This problem can be dealt with by designing media processing applications in a scalable fashion. A scalable media processing application can run in multiple qualities, leading to correspondingly different resource demands. The problem we consider is to find an accompanying quality control strategy, which minimizes both the number of deadline misses and the number of quality changes, while maximizing the quality of processing. We present an initial approach to the above problem by modeling it as a Markov decision process (MDP). Our model is based on measuring relative progress at milestones. Solving the MDP results in a quality control strategy that can be applied during runtime with only little overhead. We evaluate our approach by means of a practical example, which concerns a scalable MPEG-2 decoder.     

Discrete Wavelet Transform: Architectures, Design and Performance Issues

Due to the demand for real time wavelet processors in applications such as video compression [1], Internet communications compression [2], object recognition [3], and numerical analysis, many architectures for the Discrete Wavelet Transform (DWT) systems have been proposed. This paper surveys the different approaches to designing DWT architectures. The types of architectures depend on whether the application is 1-D, 2-D, or 3-D, as well as the style of architecture: systolic, semi-systolic, folded, digit-serial, etc. This paper presents an overview and evaluation of the architectures based on the criteria of latency, control, area, memory, and number of multipliers and adders. This paper will give the reader an indication of the advantages and disadvantages of each design.     

小波变换分离太阳射电频谱图中的纤维结构

太阳射电爆发纤维精细结构是太阳射电爆发活动中一类重要的观测现象,利用二维小波变换对纤维精细结构动态频谱图进行处理,分离频谱图中的纤维结构。首先对原始频谱图实行多层小波变换,由低频分量重构原始图像,就可得到爆发的背景信息,令原始频谱图减去背景并经过阈值处理后,便可将原始频谱图中的纤维结构很好地分离出来。     

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).     

基于开关电流技术的连续小波变换的实现方法

开关电流技术是一种新的模拟抽样数据处理技术。开关电流电路具有一般电路不具有的优点，与标准数字CMOS工艺兼容。连续小波变换是分析非平稳信号的有力工具，在信号处理上有广泛的应用。本文提出用开关电流技术实现连续小波变换的方法，并用Matlab仿真证明了其理论可行性。     

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.