Đề tài này trình bày về phương pháp DTC và việc ứng dụng Logic mờ vào phương pháp này. Tìm hiểu về DSP DS1104 và phần mềm điều khiển Control Desk. Các kết quả thể hiện qua các kết quả mô phỏng .Và thông qua hệ DSP DS1104 để điều khiển động cơ không đồng bộ thực. ABSTRACT: This paper presents about DTC control and the
Programmable Digital Signal Processors (DSPs) are pervasive in the second generation (2G) wireless handset market for digital cellular telephony. This did not come about because everyone agreed up front to use DSPs in handset architectures. Rather, it was a result of a battle between competing designs in the market place. Indeed, the full extent of the use of programmable DSPs today was probably not appreciated, even by those who were proposing DSP use, when the 2G market began to take off.
Digital Signal Processing Development System
Use of the TMS320C31 DSK Testing the software and hardware tools such as the debugger Programming examples in C and TMS320C3x code to test the tools Chapter 1 introduces several tooals available for digital signal processing (DSP). These tools include the TMS320C31-based DSP Starter Kit (DSK) with complete input and output support. Three examples are included to illustrate these development tools and, in particular, to test the DSK.
Third generation (3G) cellular systems will be based on Code Division Multiple Access (CDMA) approaches and will provide signiﬁcant data services as well as increased capacity for voice channels. This results in considerable computational requirements for 3G base stations. This chapter discusses an architecture that provides the needed computation together with signiﬁcant ﬂexibility. At the same time, this approach is one of the most cost effective known. Based upon a Texas Instruments TMS320C64xe as the core DSP, the architecture utilizes three Flexible Coprocessors (FCPs)...
Nội dung đề tài gồm có: Tổng quan về thông tin di động 3G, ứng dụng DSP khả trình trong máy cầm tay hai chế độ (2G và 3G), các DSP khả trình cho các modem trạm gốc 3G, sử dụng DSP khả trình trong xử lý dàn anten.
Increased bandwidth for Third Generation (3G) communication not only expands the capacity to support more users, but also makes it possible for network providers to offer new services with higher bit rates for multimedia applications. With increased bit rates and programmable DSPs, several new types of applications are possible for mobile devices, that include audio and video content. No longer will there be a limited 8–13 kbps, suitable only for compressed speech. At higher bit rates, the same phone’s speakers and DSP with different software can be used as a digital radio....
C Algorithms for Real-Time DSP, by Paul Embree, is a stimulating book. When I finished reading it, I went straight to my workstation and started experimenting with DSP algorithms. Embree clearly knows this subject and presents it in a straightforward manner. This is a refreshing change from the academic approach taken by the seven digital-signal processing books currently on my bookshelf. Not that Embree doesn't reference some heavy math. C Algorithms for Real-Time DSP is not for the mathematically weak of heart.
Cùng nắm kiến thức trong tài liệu "CCS4 DSP Workshop" thông qua việc tìm hiểu các nội dung sau: giới thiệu về DSP development kit, cài đặt môi trường thí nghiệm cho kit DSP DSK6416, các bài thí nghiệm DSP trên kit DSK6416.
Biological Signal Processing
At first it may seem a bit unusual to find a chapter on biological signal processing in a book dedicated to digital signal processing; yet this is in reality no more peculiar than motivating DSP by starting with the analogous principles of analog signal processing. Indeed the biological motivation should be somewhat closer to our hearts (or eyes, ears and brains). In this book we have chosen to introduce analog and digital signal processing together, but have confined our discussion of biological signal processing to this chapter....
Digital signal processing means algorithmic processing, representing signals as streams of numbers that can be manipulated by a programmable computer. Since DSP algorithms are programmed, standard computer languages may be used in principle for their implementation. In particular, block diagrams, that are conventionally used to help one grasp the essential elements of complex conventional computer programs, may be useful as DSP description and specification tools as well.
DSP Applications and Projects
This Chapter can be used as a source of experiments, projects, and applications. A wide range of projects have been implemented based on both the floatingpoint TMS320C30 digital signal processor [1–6], briefly described at the end of this chapter, and the fixed-point TMS320C25 . They range in topics from communications and controls, to neural networks, and can be used as a source of ideas to implement other projects.
‘‘DSPs take the RISC’’
From the mid-1980s to the mid-1990s, we were in the ‘‘Personal Computer’’ era and CISC microprocessors fuelled the semiconductor market growth (Figure 7.1). We are now in a new era where people demand high personalized bandwidth, multimedia entertainment and information, anywhere, anytime: Digital Signal Processing (DSP) is the driver of the new era (Figure 7.2).
In recent years, the technological trend toward high-performance mobile communications devices has caused a burgeoning interest in the ﬁeld of low-power design. Indeed, with the proliferation of portable devices such as digital cellular phones, pagers and personal digital assistants, designing for low-power with high throughput is becoming increasingly necessary. It is often claimed that a full-custom ASIC will be ‘‘lower power’’ than a programmable approach.
Báo cáo trình bày kết quả nghiên cứu và phát triển các hệ thống nhúng tiên tiến trong xây dựng các thiết bị đo lường và điều khiển thông qua cấu hình hệ thống tích hợp MDA104 và DSP cùng minh họa các phần mềm ứng dụng nhúng được thiết kế trên phần mềm công cụ nhúng cho PC104 và DSP.
Digital Filter Implementation
In this chapter we will delve more deeply into the practical task of using digital filters. We will discuss how to accurately and efficiently implement FIR and IIR filters. You may be asking yourself why this chapter is important. We already know what a digital filter is, and we have (or can find) a program to find the coefficients that satisfy design specifications. We can inexpensively acquire a DSP processor that is so fast that computational efficiency isn’t a concern, and accuracy problems can be eliminated by using floating point processors...
The Fast Fourier Transform
It is difficult to overstate the importance of the FFT algorithm for DSP. We have often seen the essential duality of signals in our studies so far; we know that exploiting both the time and the frequency aspects is critical for signal processing. We may safely say that were there not a fast algorithm for going back and forth between time and frequency domains, the field of DSP as we know it would never have developed. The discovery of the first FFT algorithm predated the availability of hardware capable of actually exploiting it. ...
Digital Signal Processors
Until now we have assumed that all the computation necessary for DSP applications could be performed either using pencil and paper or by a generalpurpose computer. Obviously, those that can be handled by human calculation are either very simplistic or at least very low rate. It might surprise the uninitiated that general-purpose computers suffer from the same limitations.
Function Evaluation Algorithms
Commercially available DSP processors are designed to efficiently implement FIR, IIR, and FFT computations, but most neglect to provide facilities for other desirable functions, such as square roots and trigonometric functions. The software libraries that come with such chips do include such functions, but one often finds these general-purpose functions to be unsuitable for the application at hand. Thus the DSP programmer is compelled to enter the field of numerical approximation of elementary functions....
The reader is provided with information on how to choose between the techniques and how to design a system that takes advantage of the best features of each of them. Imminently practical in approach, the book covers sampled data systems, choosing A-to-D and D-to-A converters for DSP applications, fast Fourier transforms, digital filters, selecting DSP hardware, interfacing to DSP chips, and hardware design techniques. It contains a number of application designs with thorough explanations.
A real-time and simultaneous processing system with 8 analog inputs is designed. The system is based on the development of Texas Instrument TMS320VC5510 DSK kit. The analog input signals are converted into digital ones by 8 bit ADC module using ADC0809. The ADC module interfaces to the DSP in parallel, through the DSP’s Memory Expansion Connector. The measurement with standard input signals fom FUNCTION GENERATOR LG1311 is also reported.