FFT Spectrum Analyzer Project for Teaching Digital Signal Processing With FPGA Devices

This paper presents a course on digital signal processing with field-programmable gate arrays (FPGA) devices. The course integrates two separate disciplines, digital signal processing (DSP) and very large scale integration (VLSI) design, and focuses on the development of a sophisticated DSP design from simulation to fixed-point implementation. The structure and methodology used in the proposed course are oriented to the design and implementation of an fast Fourier transform (FFT) spectrum analyzer. This application covers most topics included in a DSP course and gives better results that those obtained with typical courses performing independent multiple simple experiments. The project is divided into modules that show specific learning necessities and determine the course contents and organization. Each laboratory part is dedicated to design and implements the block of the analyzer related to the theoretical content presented in the class. At the end of the course the students have designed all the pieces in the DSP project and have completed and verified the system. The used methodology enables students and engineers to understand and develop complex fixed-point applications, looking for the best signal processing algorithms on hardware implementations, and also results in more motivated and active students.     

An innovative course emphasizing real-time digital signalprocessing applications

This paper presents an innovative undergraduate real-time digital signal processing (DSP) course, Digital Signal Processors, which emphases hands-on experiments and practical applications. It enables students to experiment with sophisticated DSP applications to augment the theoretical, conceptual, and analytical material provided in their first DSP course, Digital Filter Design. The inclusion of both software and hardware developmental experiences permits undergraduates to undertake a wide range of real-time DSP projects in their required Senior Engineering Design course. This paper briefly introduces representative examples of some challenging DSP applications, such as acoustic echo cancellation, active noise control, and image compression     

Robot vision with cellular neural networks: a practical implementation of new algorithms

Cellular neural networks (CNNs) are well suited for image processing due to the possibility of a parallel computation. In this paper, we present two algorithms for tracking and obstacle avoidance using CNNs. Furthermore, we show the implementation of an autonomous robot guided using only real‐time visual feedback; the image processing is performed entirely by a CNN system embedded in a digital signal processor (DSP). We successfully tested the two algorithms on this robot. Copyright © 2006 John Wiley & Sons, Ltd.     

Rapid prototyping system for teaching real-time digital signalprocessing

A low-cost rapid-prototyping system using Texas Instruments' (TI) TMS320C30 Evaluation Module (EVM) based on the MathWorks development software is presented in this paper. The rapid prototyping system serves as an educational tool in learning digital signal processing (DSP) and seeing the concept realized in real time. The development software modules, Simulink, uses graphical block diagrams to create models for real-time implementation and the real-time workshop (RTW), generates C code to be downloaded onto the EVM. The entire building process is fully automatic. This includes compiling, assembling and downloading of the real-time algorithms. The system was found to be well suited for learning real-time DSP algorithms for both undergraduate and postgraduate levels     

Power SAWs

Applications employing digital signal processing (DSP) has mushroomed over the past fifteen years. DSP techniques are now employed in television and radio receivers, in telephones, in automobile engines, in medical diagnostics, in robotics, in military systems, to just name a few. Its popularity stems from its flexibility. DSP also parallels the advances made in low cost computers and specialized integrated circuits (ICs). In a few applications, however, these digital techniques are either too slow or consume too much power to be practical. Examples include ultra-high frequency (UHF) filters and convolvers. In such applications, analog techniques can often perform the same tasks much more efficiently. Of the analog techniques, those employing surface acoustic waves (SAWs) offer unique capabilities for processing signals in the 30 MHz to 2 GHz frequency range. We examine this technology and review some of its applications     

基于DSP的高速数字电路设计中的信号完整性研究

数字信号处理芯片(DSP)是近年来迅速发展和广泛应用的高新技术,其应用领域日趋广泛,本文以TMS320VC33 DSP为处理器,设计和实现了测试系统硬件平台.高速数字电路设计中一个重要的技术难题就是如何保证信号的完整性,本文就该问题展开讨论,针对测试系统进行了信号完整性分析(SI),这对系统的抗干扰能力、可靠性的提高有很大的帮助,并对设计结果进行了仿真,证实了理论的可行性,并根据实际开发中的经验提出了在高速数字电路设计中保证信号完整性的具体措施.     

基于DSP的语音录放和数字回声的实现

数字信号处理是现代数字语音通信的核心技术之一,DSP技术的应用为实现语音信号的采集、处理和播放奠定了基础.设计基于DSP的语音信号处理系统,运用TMS320VC5416处理器和AIC23语音芯片构建出硬件平台.分析DSP处理器和Codec芯片性能特点,配置软件控制接口,实现数字音频数据通信传输.采用C语言和汇编语言混合方式编写系统主程序和模块子程序,调试实验语音处理系统的信号采集、数字回声和播放,实现语音处理系统设计功能.     

基于TM S320C6713的图像采集处理系统设计

提出了一种采用DSP、FPGA及千兆以太网的混合结构的图像采集处理系统,以FPGA作为图像采集与相机控制模块,以浮点数字信号处理器TMS320C6713为图像处理核心,以千兆以太网为传输手段,从而在硬件上解决了图像数据的采集、处理与传输的问题。该文具体阐述了系统硬件总体结构及各个模块的功能与实现方法,并讨论了嵌入式软件的结构与处理流程。     

A digital signal processing laboratory for undergraduates

An undergraduate level laboratory on digital signal processing (DSP) is described. The equipment used and samples of student experiments are described in detail. The lab is based on the TMS320 digital signal processor and is equipped with spectral analysis and audio signal processing capabilities. The primary purpose of the lab is to supplement a course on digital filter design and implementation. However, it can also be used for senior design projects involving DSP applications     

A senior project course in digital signal processing with theTMS320

A senior project course on applications in digital signal processing (DSP) with the TMS320 digital signal processor is described. All experiments and projects are performed using Texas Instruments' TMS320 digital signal processor. The laboratory emphasis in the senior project course reinforces the concepts of DSP covered in the lecture course. Applications in DSP are in areas such as communications, controls, speech, graphics, etc. The DSP projects presented and demonstrated by the students in the spring of 1987 are discussed. These projects can provide a guide to individuals who may incorporate a hands-on approach to DSP in courses such as senior project, senior lab, or DSP lab using the versatile TMS 320 digital signal processor     

Image analysis and rule-based reasoning for a traffic monitoringsystem

The paper presents an approach for detecting vehicles in urban traffic scenes by means of rule-based reasoning on visual data. The strength of the approach is its formal separation between the low-level image processing modules and the high-level module, which provides a general-purpose knowledge-based framework for tracking vehicles in the scene. The image-processing modules extract visual data from the scene by spatio-temporal analysis during daytime, and by morphological analysis of headlights at night. The high-level module is designed as a forward chaining production rule system, working on symbolic data, i.e., vehicles and their attributes (area, pattern, direction, and others) and exploiting a set of heuristic rules tuned to urban traffic conditions. The synergy between the artificial intelligence techniques of the high-level and the low-level image analysis techniques provides the system with flexibility and robustness     

基于并行数据处理结构的电能质量在线监测

提出了基于现场可编程门阵列器件FPGA与数字信号处理器DSP并行结构的在线电能质量监测与分析。由FPGA同步产生系统控制时序,并充分利用FPGA与DSP各自在数字信号处理领域中的特点,在FP GA内设计了16位浮点FFT运算模块用于谐波分析,应用DSP实现电压波动与闪变等电能质量指标数据的计算,采用FPGA与DSP并行数据处理的方式,达到采样与数据处理的同步进行的目的,从而完成对多路信号的无缝采样与分析。     

全自动数字图像畸变校正算法及其DSP实现

针对当前DSP(数字信号处理)技术的新发展,提出了基于DSP的快速图像畸变校正技术。此技术结合了当前最新的数字信号处理技术.并根据具体系统特性对现有算法进行分析、优化和改进,以最终形成具有创新性,实用性和快速性特点的算法。     

Digital input filters for measurement,control and protection of electric power systems

Power system control and protection equipment has required higher sensitivity and operational reliability than conventional one. Studies of digital signal processing suitable for electric power systems fulfill this objective using fast sampling and digital filtering by a 32-bit floating point DSP (Digital Signal Processor). The sampling rate of 3 kHz is carefully selected in order to separate the power spectrums of the A-D conversion output errors from the signal bandwidth. The new 12-bit A-D conversion unit equipped with a recursive-type digital filter achieved the equivalent high resolution of 14-bit conversion. This paper describes the design concept and the characteristics showing applications to current differential relays, distance relays and power system controllers.     

Digital input filters for measurement,control and protection in electric power systems

Power system control and protection equipment is subject to especially stringent sensitivity and operational reliability requirements. Projected digital signal processing systems suitable for electric power systems fulfill these requirements by means of fast sampling and digital filtering by a 32-bit floating point DSP (Digital Signal Processor). The sampling rate of 3 kHz is carefully selected in order to separate the power spectra of the A-D conversion output errors from the signal bandwidth. The new 12-bit A-D conversion unit equipped with a recursive-type digital filter achieved a high resolution equivalent to 14-bit conversion. This paper describes the design concept and the operating characteristics and illustrates applications to current differential relays, distance relays and power system controllers.     

DSP/BIOS在数字图像处理中的应用

采用TMS320DM642EVM作为数字图像处理硬件平台,并以数字图像边缘检测算法为例,详细阐述了DSP／BIOS程序的编写过程与程序运行过程。实验证明DSP／BIOS程序具有易于调试和维护的特点。     

The application of multi-rate digital signal processing techniquesto the measurement of power system harmonic levels

The concepts of filtering and sampling power system voltage and current signals for harmonic analysis using the fast Fourier transform (FFT) algorithm are introduced. The application of a multirate digital signal processing technique to harmonic analysis is then discussed, and the design of a polyphase decimation finite-impulse response (FIR) filter, for use as an antialiasing filter in oversampling applications, is covered. The implementation of this filter in conjunction with an FFT by a digital signal processor is described, and results of timing tests on the algorithms are presented. The instrument used to implement these techniques is an advanced data acquisition and parallel processing system aimed specifically at continuous real-time power system signal monitoring