C++ algorithms for digital signal processing

Abstract

From the Book: PREFACE: Preface This book is written with the conviction that two current trends in engineering and programming will continue in the foreseeable future and will become very closely related. The first trend is the rapidly growing importance of digital signal processing (DSP). Digital techniques have become the method of choice in signal processing as digital computers have increased in power, speed, and convenience and as powerful microprocessors have become more available. Some examples of the applications of DSP to engineering problems are: Radar signal processing such as: Synthetic aperture radar imaging Multitarget tracking Radar classification and identification Ultrasound and sonar signal processing such as: Doppler flow measurement Adaptive beam forming Image display and enhancement Image processing such as: Target recognition Pattern classification Robot vision Image compression and restoration Communications signal processing such as: Frequency hopped signal tracking Spread spectrum signal recovery Signal modulation and demodulation Adaptive equalization Geological signal processing such as: Formation identification Structure velocity estimation Speech signal processing such as: Short-time spectral analysis Speaker independent word recognition Phoneme identification Speech synthesis As DSP has engulfed signal processing, the C language is proving itself tobethe most valuable programming tool for real-time and computationally intensive software tasks. Due to the nature of DSP, this second trend is related in very important ways to the first. There are two broad areas of software applications in DSP: Applications where the software is used to simulate hardware Applications where the software is an end product in itself The C and C++ languages are reasonably high-level languages suitable for either of these areas. They have aspects of high-level languages that make them suitable for simulation work and still allow the engineer to produce code whose efficiency approaches that of assembly language for real-time applications. The C and C++ languages have significant advantages for DSP applications over other languages such as FORTRAN and Pascal. One important reason is the utility of C data structures and C++ objects for signal processing tasks. Also, the inherent modularity of C and C++ is a valuable asset in DSP programming. Digital signal processing repetitively uses a well-defined set of mathematical tools with small parameter variations. The ordering and tailoring of these algorithms to specific applications are the art of DSP. The C and C++ languages are constructed to encourage development of external library routines and objects that can be used as building blocks in the exact way required by DSP. Another reason the C++ language is a good choice for DSP is the popularity and widespread use of this language. Compilers are available for all popular microprocessors including 32-bit designs. In addition, many manufacturers of digital signal processing devices (such as Texas Instruments, AT&T, Motorola, and Analog Devices) provide C compilers for both 16-bit integer and 32-bit floating-point signal processing integrated circuits. The code produced by the best compilers is compact and efficient, and there are sufficient common features among compilers to allow portable code to be written if the standard ANSI C conventions are used. This allows the C code for DSP algorithms to be used directly in embedded real-time signal processing systems. All of the programs in this book are suitable for use with any standard ANSI C compiler on UNIX systems, IBM-PC platforms, and many real-time programming environments. Although C++ has not been the traditional language of real-time embedded systems programmers, it has been growing in popularity for application development and fast prototyping of designs. Not only does C++ allow the programmer to