The SIVA Demonstration Gallery for signal, image, and video processing education

The techniques of digital signal processing (DSP) and digital image processing (DIP) have found a myriad of applications in diverse fields of scientific, commercial, and technical endeavor. DSP and DIP education needs to cater to a wide spectrum of people from different educational backgrounds. This paper describes tools and techniques that facilitate a gentle introduction to fascinating concepts in signal and image processing. Novel LabVIEW- and MATLAB-based demonstrations are presented, which, when supplemented with Web-based class lectures, help to illustrate the power and beauty of signal and image-processing algorithms. Equipped with informative visualizations and a user-friendly interface, these modules are currently being used effectively in a classroom environment for teaching DSP and DIP at the University of Texas at Austin (UT-Austin). Most demonstrations use audio and image signals to give students a flavor of real-world applications of signal and image processing. This paper is also intended to provide a library of more than 50 visualization modules that accentuate the intuitive aspects of DSP algorithms as a free didactic tool to the broad signal and image-processing community.     

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.     

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     

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.     

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。     

Proposed network structures and combined adaptive algorithms for electrocardiogram signal denoising

An electrocardiogram (ECG) signal is a record of the electrical activities of heart muscle and is used clinically to diagnose heart diseases. An ECG signal should be presented as clear as possible to support accurate decisions made by doctors. This article proposes different combinations of combined adaptive algorithms to derive different noise-cancelling structures to remove (denoise) different kinds of noise from ECG signals. The algorithms are applied to the following types of noise: power line interference, baseline wander, electrode motion artifact, and muscle artifacts. Moreover, the results of the suggested models and algorithms are compared with those of conventional denoising tools such as the discrete wavelet transform, an adaptive filter, and a multilayer neural network (NN) to ensure the superiority of the proposed combined structures and algorithms. Furthermore, the hybrid concept is based on dual, triple, and quadruple combinations of well-known algorithms that derive adaptive filters, such as the least mean squares, normalized least mean squares and recursive least squares algorithms. The combinations are formulated based on partial update, variable step-size (VSS), and second iterative VSS algorithms, which are considered in different combinations. In addition, biased NN and unbiased linear neural network (ULNN) structures are considered. The performance of the different structures and related algorithms are evaluated by measuring the post-signal-to-noise ratio, mean square error, and percentage root mean square difference.     

光纤声发射信号采集与处理系统设计研究

针对数字式光纤声发射检测要求,本文设计了一种以DSP和CPLD为核心的信号采集与处理系统.该设计将DSP的高速信号处理能力与CPLD较强的控制能力相结合,利用DSP的DMA通道使数据采集与处理并行工作,实现信号的实时采集与处理.本文给出了系统硬件原理电路和主要的软件设计方案,讨论了CPLD时序控制设计及DSP处理系统中的关键技术问题.调试及仿真结果表明,系统具有设计简明、程序便于修改、CPU执行效率高等优点.     

Group sparse RLS algorithms

Group sparsity is one of the important signal priors for regularization of inverse problems. Sparsity with group structure is encountered in numerous applications. However, despite the abundance of sparsity‐based adaptive algorithms, attempts at group sparse adaptive methods are very scarce. In this paper, we introduce novel recursive least squares (RLS) adaptive algorithms regularized via penalty functions, which promote group sparsity. We present a new analytic approximation for ?_p,0 norm to utilize it as a group sparse regularizer. Simulation results confirm the improved performance of the new group sparse algorithms over regular and sparse RLS algorithms when group sparse structure is present. Copyright © 2013 John Wiley & Sons, Ltd.     

基于DSP的程控滤波器设计

在许多工程应用领域,信号频率的动态范围往往很宽,这时就需要采用多种截止频率的程控滤波器。用可编程DSP芯片实现数字滤波,可通过程序修改滤波器的参数,因而改变滤波器的特性十分方便,便于实现程控滤波器。本文运用以FIR滤波器为核心的设计方法,利用DSP技术实现了程控滤波器。达到了由键盘输入数据改变滤波器性能的目的,经测试整个滤波器在通带内波动较小,阻带衰减较大,运行非常稳定。     

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     

Real-time implementation of an indirect adaptive robot controller

Adaptive controllers applied to high-speed and high-precision robot manipulators give excellent tracking performances because they take into account the full dynamics of the robot. Recent publications have shown that on-line estimation of the dynamic constant parameters can be obtained by the joint tracking error (direct adaptive control) or by the torque prediction error (indirect adaptive control). In direct adaptive controllers the estimation law is derived from Lyapunov stability or Popov hyperstability methods. These controllers are simple and their real-time implementation is easy; however, the estimation is not so accurate. In indirect adaptive controllers the estimation law is based on a least squares algorithm. These controllers give accurate estimates of the manipulator parameters; however, they involve much more computation than the direct approach. Therefore no real-time implementations of indirect adaptive tracking controllers for robots have been reported in the literature until now. This paper describes a real-time implementation of an indirect adaptive scheme applied to a two-degree-of-freedom (2DOF) direct-drive SCAM robot. the controller is implemented at low cost by the use of a single-chip digital signal processor (DSP).     

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     

数字信号处理对电子测量与仪器的影响研究

数字信号处理(digital signal processing,DSP)和电子测量与仪器(electronic measurement and instrument,EMI)的关系密不可分,已是众人皆知的常识。以数字信号处理对电子测量仪器的影响为切入点,逐一探赜DSP与EMI的关系。首先说明测量的重要性,接着列举了DSP改善和提高了主要电子测量仪器的性能;最后论述了DSP突破了传统测量理论的限制,可使数字存储示波器的潜力发挥到极致。     

嵌入式谐波检测系统数据采集与实时处理的协调优化方案

提出了以数字信号处理器(digital signal processor,DSP)为内核的嵌入式系统硬件平台和以CCS(code composer studio)为编译环境的软件运行平台,分析了数据高速采集硬件构成、数字滤波程序、谐波检测分析方法、慢速设备与高速设备的连接等影响数据实时处理能力的因素,提出了用DSP实现的嵌入式谐波检测系统数据高速采集和实时处理的协调优化方案。工程实际测量结果验证了该方案的可行性和可靠性。     

Meeting the analog world challenge. Nyquist-rate analog-to-digitalconverter architectures

To bring digital processing and its benefits to bear on real-world applications, the analog signal of interest must be translated into a format a digital computer can utilize. This is the function of the analog-to-digital converter (ADC). After processing by a digital computer or digital signal processor (DSP), the resulting digital stream of information must be returned to its analog form by a digital-to-analog converter (DAC). The methods by which a digital code is generated within the ADC are diverse. We introduce three popular Nyquist-rate ADC architectures used today: the counter ramp ADC, the successive approximation ADC and the flash ADC     

A Primer on Fractions

The decision to use fixed-point arithmetic on an integer CPU or floating-point on a specialized processor is one that is common not only in digital signal processing applications, but also in many embedded applications. It is a typical engineering tradeoff fixed-point processing is cheaper, being implementable on common integer hardware, but the algorithms are complicated and the capabilities are limited; floating-point processing requires specialized hardware with additional cost, but the ease of programming and the extra range may be critical to completing the task. Other factors such as computation speed, power, and algorithm development may also be factors to consider. Your specific application may dictate which of the two you select.     

An integrated virtual learning system for the development of motordrive systems

This paper describes the basic concept of an integrated virtual learning system as an instructional tool for the development of digital signal processor (DSP)-based control schemes for motor drive applications. The system is comprised of a graphical user interface (GUI) front-end and a hardware-in-the-loop custom DSP for rapid prototyping and efficient testing of digital control algorithms. The circuit design and control algorithm development of a pulse width modulation (PWM) voltage source inverter (VSI) for 3-phase brushless DC (BLDC) motor control applications is used to describe the functions of the system. It is shown that the virtual learning system provides a cost-effective learning tool for students or engineers in training and can serve as a supplement to a conventional laboratory based system     

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.