时变带限信道中光通信的均衡与去噪技术

A semi-blind equalization method is proposed based on combination of adaptive and blind equalization techniques, which is more effective for optical signal processing in time-varied band-limited channel. The numerical simulation of Poisson noise OOK optical pulse signal in a band-limited channel using digital equalization techniques is performed, and the results are compared. The semi-blind equalization matchs the channel faster and sustains convergence were identified. In addition, the wavelet de-noise technique is introduced in the de-nosing area of optical signa process. The criteria of choosing wavelet basises is obtained that smooth wavelet soft threshold method is better. The corresponding numerical simulation is also conducted.

用VHDL实现的23位快速浮点数加减法器

With the development of LSI, FPGA/CPLD has been used more and more in the fields of digital signal processing and au-tocontrol and so on. And with the development of the techniques of digital processing, for fitting the system’s function, it should be a higher requirement to speed and used-resource to compute the floating point numbers. The author introduces a high speed adder-subtracter of the 23 bit’s floating point numbers, which is carried out with the parallel arithmetic and the computational speed cou...中文文摘：随着大规模集成电路的不断发展,FPGA/CPLD在数字信号处理、自动控制等方面得到了越来越多的应用。并且伴随着数字化处理技术的不断发展,为满足系统功能的要求,对浮点数运算的速度以及相应占用的资源也就提出了更高的要求。笔者即介绍了以VHDL语言为基础,采用并行算法且计算速度达到33MHz的,对23位标准浮点数实现的高速浮点加减法运算器,并以Cyclone II芯片EP2C20F484为硬件环境,最终进行时序模拟仿真,从而验证该浮点加减法器的正确性和快速特性。

Recent progress in femtosecond holography

The recent advancements of femtosecond (fs) holography are introduced. The experimental requirements and the time resolution are presented. Applications of femtosecond holography to signal processing, and other femtosecond holographic techniques such as femtosecond holographic imaging and microprocessing are detailed. A potential alternative of femtosecond holography is proposed, based on the sectional interference of reference pulse with the time stretched signal pulse. (c) 2005 Elsevier B.V. All rights reserved.

反水雷与UxV

反水雷作战是一项极其危险的作战任务,而无人作战平台(UxV)的特点决定了其可以降低甚至消除这种危险性,因此在反水雷作战中使用UxV成为必然的发展趋势。本文分析了反水雷作战的特点、各种UxV的特点及其在反水雷作战中的优势,并根据反水雷的需求提出了在UxV中需重点解决的智能控制技术、精确导航与定位技术、传感器及信号处理技术等关键技术。

基于匹配追踪方法的地震信号时频分析研究

Seismic signal is a typical non-stationary signal, whose frequency is continuously changing with time and is determined by the bandwidth of seismic source and the absorption characteristic of the media underground. The most interesting target of seismic signal’s processing and explaining is to know about the local frequency’s abrupt changing with the time, since this kind of abrupt changing is indicating the changing of the physical attributes of the media underground. As to the seismic signal’s instantaneous attributes taken from time-frequency domain, the key target is to search a effective, non-negative and fast algorithm time-frequency distribution, and transform the seismic signal into this time-frequency domain to get its instantaneous power spectrum density, and then use the process of weighted adding and average etc. to get the instantaneous attributes of seismic signal. Time-frequency analysis as a powerful tool to deal with time variant non-stationary signal is becoming a hot researching spot of modern signal processing, and also is an important method to make seismic signal’s attributes analysis. This kind of method provides joint distribution message about time domain and frequency domain, and it clearly plots the correlation of signal’s frequency changing with the time. The spectrum decomposition technique makes seismic signal’s resolving rate reach its theoretical level, and by the method of all frequency scanning and imaging the three dimensional seismic data in frequency domain, it improves and promotes the resolving abilities of seismic signal vs. geological abnormal objects. Matching pursuits method is an important way to realize signal’s self-adaptive decomposition. Its main thought is that any signal can be expressed by a series of time-frequency atoms’ linear composition. By decomposition the signal within an over completed library, the time-frequency atoms which stand for the signal itself are selected neatly and self-adaptively according to the signal’s characteristics. This method has excellent sparse decomposition characteristics, and is widely used in signal de-noising, signal coding and pattern recognizing processing and is also adaptive to seismic signal’s decomposition and attributes analysis. This paper takes matching pursuits method as the key research object. As introducing the principle and implementation techniques of matching pursuits method systematically, it researches deeply the pivotal problems of atom type’s selection, the atom dictionary’s discrete, and the most matching atom’s searching algorithm, and at the same time, applying this matching pursuits method into seismic signal’s processing by picking-up correlative instantaneous messages from time-frequency analysis and spectrum decomposition to the seismic signal. Based on the research of the theory and its correlative model examination of the adaptively signal decomposition with matching pursuit method, this paper proposes a fast optimal matching time-frequency atom’s searching algorithm aimed at seismic signal’s decomposition by frequency-dominated pursuit method and this makes the MP method pertinence to seismic signal’s processing. Upon the research of optimal Gabor atom’s fast searching and matching algorithm, this paper proposes global optimal searching method using Simulated Annealing Algorithm, Genetic Algorithm and composed Simulated Annealing and Genetic Algorithm, so as to provide another way to implement fast matching pursuit method. At the same time, aimed at the characteristics of seismic signal, this paper proposes a fast matching atom’s searching algorithm by means of designating the max energy points of complex seismic signal, searching for the most optimal atom in the neighbor area of these points according to its instantaneous frequency and instantaneous phase, and this promotes the calculating efficiency of seismic signal’s matching pursuit algorithm. According to these methods proposed above, this paper implements them by programmed calculation, compares them with some open algorithm and proves this paper’s conclusions. It also testifies the active results of various methods by the processing of actual signals. The problems need to be solved further and the aftertime researching targets are as follows: continuously seeking for more efficient fast matching pursuit algorithm and expanding its application range, and also study the actual usage of matching pursuit method.