C++ Algorithms for Digital Signal Processing (inbunden)
Inbunden (Hardback)
Antal sidor
Prentice Hall
Danieli, Damon
240 x 190 x 25 mm
1100 g
Antal komponenter
with CD-ROM

C++ Algorithms for Digital Signal Processing

Inbunden, Engelska, 1998-11-01
1004 kr
Specialorder (osäker tillgång). Skickas inom 11-20 vardagar.
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Bring the power and flexibility of C++ to all your DSP applications

The multimedia revolution has created hundreds of new uses for Digital Signal Processing, but most software guides have continued to focus on outdated languages such as FORTRAN and Pascal for managing new applications. Now C++ Algorithms for Digital Signal Processing applies object-oriented techniques to this growing field with software you can implement on your desktop PC. C++ Algorithms for Digital Signal Processing's programming methods can be used for applications as diverse as:

  • Digital audio and video
  • Speech and image processing
  • Digital communications
  • Radar, sonar, and ultrasound signal processing
Complete coverage is provided, including:

  • Overviews of DSP and C++
  • Hands-on study with dozens of exercises
  • Extensive library of customizable source code
  • Import and Export of Microsoft WAV and Matlab data files
Multimedia professionals, managers, and even advanced hobbyists will appreciate C++ Algorithms for Digital Signal Processing as much as students, engineers, and programmers. It's the ideal bridge between programming and signal processing, and a valuable reference for experts in either field.
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List of Key Symbols.

1. Digital Signal Processing Fundamentals.


The Sampling Function. Sampled Signal Spectra. Continuous- and Discrete Time Signal Spectra. The Impulse Sequence.

Linear Time Invariant Operators.

Causality. Difference Equations. The z-transform Description of Linear Operators. Frequency Domain Transfer Function of an Operator. Frequency Response Relationship to the z-transform. Summary of Linear Operators.

Digital Filters.

FIR Filters. Linear Phase in FIR Filters. IIR Filters. Example Filter Responses. Filter Specifications. Filter Structures.

The Discrete Fourier Transform.

Form of the DFT. Properties of the DFT. Power Spectrum. Averaged Periodograms. The Fast Fourier Transform. FFT Example Result.

Nonlinear Operators.

Clipping and Compression. _-law and A-law Compression. Filtering by Sorting: Median and Min/Max Filters.

Linear Algebra: Matrices and Vectors.

Vectors. Properties of Matrix Mathematics.

Probability and Random Processes.

Basic Probability. Random Variables. Mean, Variance, and Gaussian Random Variables. Quantization of Sequences. Random Processes, Autocorrelation, and Spectral Density. Modeling Real-World Signals With AR Processes.

Adaptive Filters and Systems.

Wiener Filter Theory. LMS Algorithms.

Two-Dimensional Signal Processing.

The Two-Dimensional Fourier Transform. Two-Dimensional Convolution. Using the FFT to Speed Up Two-Dimensional Processing. Two-Dimensional Filtering in the Transform Domain.


2. Programming Fundamentals.

The Elements of DSP Programming. Variables and Data Types.

Types of Numbers. Arrays. Text Data Types: Characters and Strings.


Assignment Operators. Arithmetic and Bitwise Operators. Combined Operators. Logical Operators. Operator Overloading. Operator Precedence and Type Conversion.

Program Control.

Conditional Execution: if-else. The switch Statement. Single-Line Conditional Expressions. Loops: while, do-while, and for. Program Jumps: break, continue, and goto. Exception Handling.


Defining and Declaring Functions. Storage Class, Privacy, and Scope. Function Prototypes. Templates.

Macros and the C Preprocessor.

Conditional Preprocessor Directives. Macros. Inline Functions. Constant Variables.

Pointers, Arrays, and References.

Special Pointer Operators. Pointers and Dynamic Memory Allocation. Arrays of Pointers. References.


Declaring and Referencing Structures. Member Functions. Constructors and Destructors. Pointers to Structures.