ORIGIN OF DIGITAL SIGNAL PROCESSING
MOTOROLA
DSP56K FAMILY INTRODUCTION 1 - 7
Digital Filtering
Finite Impulse Response (FIR)
Infinite Impulse Response (IIR)
Matched Filters (Correlators)
Hilbert Transforms
Windowing
Adaptive Filters/Equalizers
Signal Processing
Compression (e.g., Linear Predictive
Coding of Speech Signals)
Expansion
Averaging
Energy Calculations
Homomorphic Processing
Mu-law/A-law to/from Linear Data
Conversion
Data Processing
Encryption/Scrambling
Encoding (e.g., Trellis Coding)
Decoding (e.g., Viterbi Decoding)
Useful applications are based on combining these and other functions. DSP applications
affect almost every area in electronics because any application for analog electronic cir-
cuitry can be duplicated using DSP. The advantages in doing so are becoming more
compelling as DSPs become faster and more cost effective.Some typical applications for
DSPs are presented in the following list:
Numeric Processing
Scaler, Vector, and Matrix Arithmetic
Transcendental Function Computation
(e.g., Sin(X), Exp(X))
Other Nonlinear Functions
Pseudo-Random-Number Generation
Modulation
Amplitude
Frequency
Phase
Spectral Analysis
Fast Fourier Transform (FFT)
Discrete Fourier Transform (DFT)
Sine/Cosine Transforms
Moving Average (MA) Modeling
Autoregressive (AR) Modeling
ARMA Modeling
Telecommunication
Tone Generation
Dual-Tone Multifrequency (DTMF)
Subscriber Line Interface
Full-Duplex Speakerphone
Teleconferencing
Voice Mail
Adaptive Differential Pulse Code
Modulation (ADPCM) Transcoder
Medium-Rate Vocoders
Noise Cancelation
Repeaters
Integrated Services Digital Network
(ISDN) Transceivers
Secure Telephones
Data Communication
High-Speed Modems
Multiple Bit-Rate Modems
High-Speed Facsimile
Radio Communication
Secure Communications
Point-to-Point Communications
Broadcast Communications
Cellular Mobile Telephone
Computer
Array Processors
Work Stations
Personal Computers
Graphics Accelerators