Realtime digital signal processing system using a parallel processing architecture

A low cost, high-speed, general-purpose ditigal signal processing system was constructed using the TMS32010 digital signal processor. The system was designed with simplicity, compactness, flexibility and expandibility in mind. A parallel processing architecture was adopted to achieve realtime performance. Four processors were used in the prototype system, but this can be expanded easily. Interprocessor data transfer and communications with the host computer are facilitated via a single common bus and a bank of shared memory. A one-dimensional digital FIR filter and a realtime FFT program were used to evaluate the performance of the system. In addition, a realtime spectrogram was implemented as an application example.     

TMS 320—a step forward in digital signal processing

Despite the numerous advantages of digital signal processing (DSP), and the existence of a wealth of sophisticated algorithms, the widespread application of DSP has been hindered by a shortage of cost-effective digital hardware for volume use. Now, with the availability of low-cost high-speed VLSI circuits, such as the Texas Instruments TMS320, the virtues and power of DSP are ready for realtime signal processing applications.Development of the single-chip TMS320 DSP computer began in the late 1970s. The architecture, key novel features, instruction set and capabilities of this device are examined. Support software and hardware development tools for the TMS320 are also included with some of its applications. Typical areas of application of the TMS320 include speech signal processing, telecommunications, robotics, radar signal and sonar signal processing, seismology, image processing, audio recording and reproduction, biomedical instrumentation, acoustic noise measurements and automatic test equipment.     

A software design for microcomputer based digital instrumentation scheme using a spectral observer

This paper presents a new recursive discrete-time filter for real-time monitoring of voltage, current, active and reactive power of an electrical/electronic network using a spectral observer. From a signal model comprising a decaying d.c., fundamental and harmonic components, an interpolating spectral observer is constructed to give the desired Fourier coefficients recursively. Initially, a dead beat spectral observer is designed with different sampling rates for the digital instrumentation scheme. Further, the performance of the spectral observer has been studied by placing the poles of the observer at locations other than the origin of the (Z-plane) complex plane.

The fast computational processing capability of this algorithm makes it suitable for microprocessor applications. This digital instrumentation scheme is tested in real-time for a laboratory electrical network using an LSI-11/23, 16-bit microcomputer.     

FAD-flexibility in digital signal processing

A digital filter and detection chip (FAD) has been developed by British Telecom in the UK for application as a tone detector in digital telephone exchanges. The chip has a flexible structure and has since found application in many other communication systems. This paper describes the chip and indicates how it can be used to perform a variety of different algorithms for these purposes.     

对“按频率抽取的RBFFT算法”一文的修正

本文首先修正了“按频率抽取的RB FFT算法”一文中的错误,然后给出了RB FFT算法的另一个矩阵分解公式。按该公式进行计算所需运算量比按文[1]给出的两种都要少。     

用MAX7000A实现多普勒信号数字信号处理的分析与线路设计

本文以连续波多普勒无线电引信为研究背景,建立目标信号数学模型,针对目前炸高控制方法及存在问题,提出了一种新的多普勒脉宽技术测高方法,在此基础上增加一个近表面炸的性能。并介绍了采用可编程逻辑器件实现的方法以及计算机仿真。实践证明,对Ｄｏｐｐｌｅｒ信号的数字信息处理,用一片ＣＰＬＤ实现,提高引信信号处理的速度,并极大提高了系统的可靠性。     

TMS320 digital signal processor development system

Digital signal processing using special processors seems to have an important future. The TMS320 is one of the best known of such processors. Experiences of building and using TMS320 development tools — a simulator and a ROM emulator — in a university environment are described. Conclusions drawn from this work are presented and possible further avenues of exploration are indicated.     

Realtime high resolution data acquisition unit for an MC68000 system

The general procedure for data acquisition in digital signal processing systems is to acquire a block of data and then analyse it. In a single-processor system, a considerable amount of data can be lost because, while data is being analysed by the processor, it is not sampled from the A/D converter. A dual-tasking machine has therefore been developed for continuous data analysis. The design requirements of the system are discussed. A block diagram of the system is presented, and the analogue-to-digital converter board is described in detail. The memory interchange board is also considered in depth.     

基于小波包分析的数字信号处理

小波包分析具有优良的时频特性,可以有效地用于数字信号的消噪处理和对信号进行特征提取。小波包分析可以对电机振动故障进行诊断,以便随时排除故障。同时,给出并分析了试验结果。     

电力智能传感器中的信号处理研究

探讨了误差最小均方(LMS)法在电力智能传感器的电压分量中的运用。提出并分析和比较了获取电力智能传感器中电压有效值和初始相位角的几种方法,指出误差LMS法因降低了对电路性能的要求而能有效地简化系统、降低成本。仿真实验表明:直接根据定义分析电力参数,需要很高的采样频率与信噪比,而利用误差LMS法在获取电压有效值时采样频率可降低3倍,在求解初始相位角时对信号中干扰幅值的要求从小于信号幅值的5%可放宽到信号幅值的15%。     

The construction of wavelet network for speech signal processing

Wavelet decomposition reconstructs a signal by a series of scaled and translated wavelets. Incorporating discrete wavelet decomposition theory with neural network techniques, wavelet networks have recently emerged as a powerful tool for many applications in the field of signal processing, such as data compression and function approximation. In this paper, four contributions are claimed: (1) From the point of view of machine learning, we analyse and construct wavelet network to achieve the compact representation of a signal. (2) A new algorithm of constructing wavelet network is proposed. The orthogonal least square (OLS) is employed to prune the wavelet network. (3) Our experiments on speech signal processing results show that the wavelet network pruned by OLS achieves the best approximation and prediction capabilities among the representative speech processing techniques. (4) Our proposed methodology has been successfully applied to speech synthesis for a talking head to read web texts.     

Research progress of the fractional Fourier transform in signal processing

While solving a heat conduction problem in 1807, a French scientist Jean Baptiste Jo-seph Fourier, suggested the usage of the Fourier theorem. Thereafter, the Fourier trans-form (FT) has been applied widely in many scientific disciplines, and has played i…     

我国雷达信号处理研究文献的计量统计分析

采用文献计量学的原理,以CNKI数据库中的中国期刊全文数据库作为统计源,对1999年～2008年收录在我国核心期刊上的雷达信号处理研究领域的论文,从时间分布、期刊分布、关键词词频、论文作者统计、合著分布及作者机构分布等方面进行统计分析,从一个侧面反映我国雷达信号处理研究的现状和发展趋势。     

Low power architectures for digital signal processing

Low power architectures for digital signal processing algorithms requiring inner product computation are presented. In the first step a power efficient memory organization exploiting data reuse is determined. In the second step an order of evaluation of the partial products that reduces the switching activity at the inputs of the computational units is derived. Information related to both coefficients which are static and data which are dynamic, is used to drive the reordering of computation. Experimental results for several signal processing algorithms prove that the proposed techniques lead to significant savings in net switching activity and thus in power consumption.     

一种基于数字AGC的定点字长控制算法研究与实现

对数字信号处理中定点计算字长保留问题进行了研究.首先分析了定点计算中截短量化噪声、保留字长与信噪比损失的关系;而后针对信号定点处理中的多次字长截短问题,给出一种基于数字AGC的字长截短控制算法,并在FPGA硬件平台上对算法进行了验证.理论分析和验证结果表明,该算法能够适应输入信号的变化,保证处理流程中的有效量化位数与量化信噪比.     

一种快速离散小波变换算法及其在语音信号中的应用

随着小波分析的理论研究水平不断提高,其应用领域也在不断扩展。特别是其多分辨率分析和Mallat算法在数字信号处理和数字通信中得到了广泛的应用。但是如果直接按照上述算法计算信号的小波分解和重构,其计算量将是很大的。通过对实序列的快速傅里叶变换(FFT)算法的推导及Mallat算法原理的分析,根据离散小波变换算法结构特征,提出了一种基于FFT的快速离散小波变换算法,并从数学理论上进行了论证。同时把该算法应用到实际的语音信号处理中,得到了很好的快速分解和重构效果。     

基于数字平方算法的APSK信号位定时误差估计方法

APSK高阶调制用于卫星通信时,信号受收发系统的时钟频差影响严重,同步算法也较为复杂。介绍了APSK的信号模型,在此基础上,采用一种数字平方算法估计位定时的误差。仿真结果表明,该方法能较好地估计出APSK信号位定时误差,且算法不受载波频偏的影响。通过仿真得出了算法性能与运算数据长度的关系。     

LabVIEW在数字信号处理教学中的应用

针对数字信号处理教学的现状和存在的问题及LabVIEW软件的功能,提出了将LabVIEW应用于数字信号处理的教学中。并以滤波器设计与帕塞瓦尔定理验证的LabVIEW辅助教学为例,指出将LabVIEW运用于数字信号处理教学中的优点和该方法的可行性。     

Dynamic network signal processing using latent threshold models

We discuss multivariate time series signal processing that exploits a recently introduced approach to dynamic sparsity modelling based on latent thresholding. This methodology induces time-varying patterns of zeros in state parameters that define both directed and undirected associations between individual time series, so generating statistical representations of the dynamic network relationships among the series. Following an overview of model contexts and Bayesian analysis for dynamic latent thresholding, we exemplify the approach in two studies: one of foreign currency exchange rate (FX) signal processing, and one in evaluating dynamics in multiple electroencephalography (EEG) signals. These studies exemplify the utility of dynamic latent threshold modelling in revealing interpretable, data-driven dynamics in patterns of network relationships in multivariate time series.     

多媒体信号处理的数学理论前沿进展

深度学习模型广泛应用于多媒体信号处理领域,通过引入非线性能够极大地提升性能,但是其黑箱结构无法解析地给出最优点和优化条件。因此如何利用传统信号处理理论,基于变换/基映射模型逼近深度学习模型,解析优化问题,成为当前研究的前沿问题。本文从信号处理的基础理论出发,分析了当前针对高维非线性非规则结构方法的数学模型和理论边界,主要包括：结构化稀疏表示模型、基于框架理论的深度网络模型、多层卷积稀疏编码模型以及图信号处理理论。详细描述了基于组稀疏性和层次化稀疏性的表示模型和优化方法,分析基于半离散框架和卷积稀疏编码构建深度/多层网络模型,进一步在非欧氏空间上扩展形成图信号处理模型,并对国内外关于记忆网络的研究进展进行了比较。最后,展望了多媒体信号处理的理论模型发展,认为图信号处理通过解析谱图模型的数学性质,解释其中的关联性,为建立广义的大规模非规则多媒体信号处理模型提供理论基础,是未来研究的重要领域之一。