
B. Tech. - Government College of Engineering Amravati
... Extensive use of MATLAB should be done for imparting instructions Introduction to Signals and Systems: •Signals and Systems, Classification of Signals Classification of Systems, Systems Modeling Some Ideal Signals, Energy and Power Signals Frequency Response, Discrimination of Continuous-Time Signal ...
... Extensive use of MATLAB should be done for imparting instructions Introduction to Signals and Systems: •Signals and Systems, Classification of Signals Classification of Systems, Systems Modeling Some Ideal Signals, Energy and Power Signals Frequency Response, Discrimination of Continuous-Time Signal ...
ADC, FFT and Noise. p. 1 ADC, FFT, and Noise
... takes the fast Fourier transform (FFT) of a specified number samples of the waveform, and (3) displays the Fourier transform on the monitor. For the number of samples always use a number that is a power of 2, i.e. 2n, because the FFT program works much more efficiently on such a sample. ...
... takes the fast Fourier transform (FFT) of a specified number samples of the waveform, and (3) displays the Fourier transform on the monitor. For the number of samples always use a number that is a power of 2, i.e. 2n, because the FFT program works much more efficiently on such a sample. ...
Chirp spectrum

The spectrum of a chirp pulse describes its characteristics in terms of its frequency components. This frequency-domain representation is an alternative to the more familiar time-domain waveform, and the two versions are mathematically related by the Fourier transform. The spectrum is of particular interest when pulses are subject to signal processing. For example, when a chirp pulse is compressed by its matched filter, the resulting waveform contains not only a main narrow pulse but, also, a variety of unwanted artifacts many of which are directly attributable to features in the chirp's spectral characteristics. The simplest way to derive the spectrum of a chirp, now computers are widely available, is to sample the time-domain waveform at a frequency well above the Nyquist limit and call up an FFT algorithm to obtain the desired result. As this approach was not an option for the early designers, they resorted to analytic analysis, where possible, or to graphical or approximation methods, otherwise. These early methods still remain helpful, however, as they give additional insight into the behavior and properties of chirps.