# Binary code digital signal processing principles algorithms and applications

Quantization effects that are inherent in the AID conversion of a signal were also introduced in this chapter. Signal quantization is best treated in statistical terms. There are numerous pracrjcal applications of digital signal processing. The book edited by Oppenheim treats appIications to speech processing, image processing, radar signal processing, sonar signal processing, and geophysical signal processing. Give a brief explanation. Sketch x n on the same diagram with x, r.

What is the period of the discrete-time signal in milliseconds? What is the minimum F, suitable for t h s task? What is the highest frequency that can be represented uniquely at this sampling rate?

Determine the output y,, r of the system. U a Derive the expression for the discrete-time signal x n in Example 1. How many bits are required in the A D converter in each case? Sinusoidal signals were introduced primarily for the purpose of illustrating the aliasing phenomenon and for the subsequent development of the sampling theorem.

Quantization effects that are inherent in the AID conversion of a signal were also introduced in this chapter. Signal quantization is best treated in statistical terms. There are numerous pracrjcal applications of digital signal processing. The book edited by Oppenheim treats appIications to speech processing, image processing, radar signal processing, sonar signal processing, and geophysical signal processing. Give a brief explanation. Sketch x n on the same diagram with x, r.

What is the period of the discrete-time signal in milliseconds? What is the minimum F, suitable for t h s task? What is the highest frequency that can be represented uniquely at this sampling rate? Determine the output y,, r of the system. U a Derive the expression for the discrete-time signal x n in Example 1.