Mixed-signal and DSP Design Techniques PDF

Download Mixed-signal and DSP Design Techniques PDF book free online – From Mixed-signal and DSP Design Techniques PDF: 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. Heavily illustrated, the book contains all the design reference information that engineers need when developing mixed and digital signal processing systems.

From the Back Cover

*Brought to you from the experts at Analog Devices, Inc.
*A must for any electrical, electronics or mechanical engineer’s reference shelf
*Design-oriented, practical volume

Mixed-signal processing implies the use of both analog and digital in the same system; this is a specialized type of signal processing that requires a high level of experience and training. Knowledge of digital signal processing (DSP) techniques is now becoming a requirement of almost every engineer. Analog Devices’ Mixed-signal and DSP Design Techniques focuses primarily on signal processing hardware—how it works, how to interface to it, and how to design it and debug it.

This is the first volume in a new Newnes professional/reference series in partnership with Analog Devices. Analog Devices Inc. (ADI) is an S&P 500 company with annual revenues over $2 billion, headquartered in Norwood, MA, and are the acknowledged world authorities on data conversion and signal processing. Many of the world’s foremost experts on analog, digital, and mixed signal processing are employed by Analog Devices, and they have contributed to this volume.

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. Heavily illustrated, the book contains all the design reference information that engineers need when developing mixed and digital signal processing systems.|*Brought to you from the experts at Analog Devices, Inc.
*A must for any electrical, electronics or mechanical engineer’s reference shelf
*Design-oriented, practical volume

Mixed-signal processing implies the use of both analog and digital in the same system; this is a specialized type of signal processing that requires a high level of experience and training. Knowledge of digital signal processing (DSP) techniques is now becoming a requirement of almost every engineer. Analog Devices’ Mixed-signal and DSP Design Techniques focuses primarily on signal processing hardware—how it works, how to interface to it, and how to design it and debug it.

This is the first volume in a new Newnes professional/reference series in partnership with Analog Devices. Analog Devices Inc. (ADI) is an S&P 500 company with annual revenues over $2 billion, headquartered in Norwood, MA, and are the acknowledged world authorities on data conversion and signal processing. Many of the world’s foremost experts on analog, digital, and mixed signal processing are employed by Analog Devices, and they have contributed to this volume.

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. Heavily illustrated, the book contains all the design reference information that engineers need when developing mixed and digital signal processing systems.

About the Author

An S&P 500 company with annual revenues over $2 billion, headquartered in Norwood, MA, an industry leader in analog, digital, and mixed signal processing technology.

Mixed-Signal and DSP Design Contents


  • Sampled-Data Systems
  • ADCs for DSP Applications
  • DACs for DSP Applications
  • Fast Fourier Transforms
  • Digital Filters
  • DSP Hardware
  • Interfacing to DSPs
  • DSP Applications
  • Hardware Design Techniques

Introduction to Mixed-Signal and DSP Design Techniques PDF


In this book, we will primarily be dealing with the processing of real-world signals using both analog and digital techniques. Before starting, however, let’s look at a few key concepts and definitions required to lay the groundwork for things to come.

Key to this definition is the words: detectable, a physical quantity, and information. By their very nature, signals are analog, whether dc, ac, digital levels, or pulses.

It is customary, however, to differentiate between analog and digital signals in the following manner: Analog (or real-world) variables in nature include all measurable physical quantities.

The entire subject of signal conditioning deals with preparing real-world signals for processing and includes such topics as sensors (temperature and pressure, for example), isolation amplifiers, and instrumentation amplifiers. (Reference 1.) Some signals result in response to other signals.

A good example is the returned signal from a radar or ultrasound imaging system, both of which result from a known transmitted signal.

On the other hand, there is another classification of signals, called digital, where the actual signal has been conditioned and formatted into a digit. These digital signals may or may not be related to real-world analog variables.

Examples include the data transmitted over local area networks (LANs) or other high-speed networks. In the specific case of digital signal processing (DSP), the analog signal is converted into binary form by a device known as an analog-to-digital converter (ADC).

The output of the ADC is a binary representation of the analog signal and is manipulated arithmetically by the digital signal processor. After processing, the information obtained from the signal may be converted back into the analog form using a digital-to-analog converter (DAC).

Another key concept embodied in the definition of the signal is that there is some kind of information contained in the signal. This leads us to the key reason for processing real-world analog signals: the extraction of information.

The primary reason for processing real-world signals is to extract information from them. This information normally exists in the form of signal amplitude (absolute or relative), frequency or spectral content, phase, or timing relationships with respect to other signals.

Once the desired information is extracted from the signal, it may be used in a number of ways. In some cases, it may be desirable to reformat the information contained in a signal.

This would be the case in the transmission of a voice signal over a frequency division multiple access (FDMA) telephone system. In this case, analog techniques are used to “stack” voice channels in the frequency spectrum for transmission via microwave relay, coaxial cable, or fiber.

In the case of a digital transmission link, the analog voice information is first converted into digital using an ADC.

The digital information representing the individual voice channels is multiplexed in time (time division multiple access, or TDMA) and transmitted over a serial digital transmission link (as in the T-carrier system).

Another requirement for signal processing is to compress the frequency content of the signal (without losing significant information), then format and transmit the information at lower data rates, thereby achieving a reduction in required channel bandwidth.

High-speed modems and adaptive pulse code modulation systems (ADPCM) make extensive use of data reduction algorithms, as do digital mobile radio systems, MPEG recording and playback, and high definition television (HDTV).

Industrial data acquisition and control systems make use of information extracted from sensors to develop appropriate feedback signals which in turn control the process itself.

Note that these systems require both ADCs and DACs as well as sensors, signal conditioners, and the DSP (or microcontroller).

Analog Devices offers a family of MicroConverters™ that includes precision analog conditioning circuitry, ADCs, DACs, microcontroller, and FLASH memory all on a single chip. In some cases, the signal containing the information is buried in noise, and the primary objective is signal recovery.

Techniques such as filtering, autocorrelation, and convolution are often used to accomplish this task in both the analog and digital domains. In most of the above examples (the ones requiring DSP techniques), both ADCs and DACs are required.

In some cases, however, only DACs are required where real-world analog signals may be generated directly using DSP and DACs. Video raster scan display systems are a good example. The digitally generated signal drives a video or RAMDAC.

Another example is artificially synthesized music and speech. In reality, however, the real-world analog signals generated using purely digital techniques do rely on information previously derived from the real-world equivalent analog signals.

In-display systems, the data from the display must convey the appropriate information to the operator. In synthesized audio systems, the statistical properties of the sounds being generated have been previously derived using extensive DSP analysis of the entire signal chain, including sound source, microphone, preamp, and ADC.

Signals may be processed using analog techniques (analog signal processing, or ASP), digital techniques (digital signal processing, or DSP), or a combination of analog and digital techniques (mixed-signal processing, or MSP).

In some cases, the choice of techniques is clear; in others, there is no clear-cut choice, and second-order considerations may be used to make the final decision.

With respect to DSP, the factor that distinguishes it from traditional computer analysis of data is its speed and efficiency in performing sophisticated digital processing functions such as filtering, FFT analysis, and data compression in real-time.

The term mixed-signal processing implies that both analog and digital processing are done as part of the system.

The system may be implemented in the form of a printed circuit board, hybrid microcircuit, or a single integrated circuit chip. In the context of this broad definition, ADCs and DACs are considered to be mixed-signal processors, since both analog and digital functions are implemented in each.

Recent advances in very large scale integration (VLSI) processing technology allow complex digital processing as well as analog processing to be performed on the same chip. The very nature of DSP itself implies that these functions can be performed in real-time. 

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