Comparison of Cellular Automata and DSP Processors towards DSP Application

Abstract

In this paper we have emphasized on alternative uses of Cellular Automata (CA) in Digital Signal Processing (DSP). The corollary of the distinction is centered on the parallel nature for both of the processors. For digital signal processing, parallelism has been focused with reference to hardware parallelism as well as software parallelism. Major issues for DSP implementation i.e. sampling, superposition, decomposition, Fourier transformation using CA have been covered in this paper (1). Those discussed results ensure that CA is much efficient to be used for DSP Implementation instead of DSP processors. An ADC transforms an analog signal into digital by choosing sample of the signal at regular intervals and providing the results as a 1D array with suitable sampling frequency, which is determined by Shannon's sampling theorem. By Shannon's sampling theorem, it is essential to sample a signal at a rate greater than double the highest frequency component in the signal in order to keep all the frequency components. In supplementary words, if a signal is sampled at a frequency less than twice the highest frequency of the signal, it may be impossible for a DSP to reproduce the analog waveform from the sampled data precisely.