Digital Signal Processing and Filter Design using Scilab

Digital Signal Processing and Filter Design using Scilab

49 Pages · 2010 · 452 KB · English

Digital Signal Processing and Filter Design using Scilab Digital Signal Processing and Filter Design using Scilab Iman Mukherjee Department of Electrical Engineering

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Digital Signal Processing and Filter Design using Scilab Digital Signal Processing and Filter Design using Scilab Iman Mukherjee Department of Electrical Engineering, IIT Bombay December 1, 2010 Iman Mukherjee Digital Signal Processing and Filter Design using Scilab Digital Signal Processing and Filter Design using Scilab Outline 1 Basic signal processing tools Discrete Fourier Transform Fast Fourier Transform Convolution Plotting Group Delay Aliasing 2 Filter Design NonRecipe Based Recipe Based An Example Application Iman Mukherjee Digital Signal Processing and Filter Design using Scilab Digital Signal Processing and Filter Design using Scilab Basic signal processing toolsDiscrete Fourier Transform DFT X (! ) = 1 X n = 1 x [n ]e j !n The Scilab command 99K[xf ] = dft(x, ag); x is the time domain representation xf is the frequency domain representation ag = 1 or 1 Notice Cosine is Even Symmetric, hence this 64point DFT is real with peaks at 4 and 60 (644) Faster way t Iman Mukherjee Digital Signal Processing and Filter Design using Scilab Digital Signal Processing and Filter Design using Scilab Basic signal processing toolsDiscrete Fourier Transform DFT X (! ) = 1 X n = 1 x [n ]e j !n The Scilab command 99K[xf ] = dft(x, ag); x is the time domain representation xf is the frequency domain representation ag = 1 or 1 Notice Cosine is Even Symmetric, hence this 64point DFT is real with peaks at 4 and 60 (644) Faster way t Iman Mukherjee Digital Signal Processing and Filter Design using Scilab Digital Signal Processing and Filter Design using Scilab Basic signal processing toolsDiscrete Fourier Transform DFT X (! ) = 1 X n = 1 x [n ]e j !n The Scilab command 99K[xf ] = dft(x, ag); x is the time domain representation xf is the frequency domain representation ag = 1 or 1 Notice Cosine is Even Symmetric, hence this 64point DFT is real with peaks at 4 and 60 (644) Faster way t Iman Mukherjee Digital Signal Processing and Filter Design using Scilab Digital Signal Processing and Filter Design using Scilab Basic signal processing toolsDiscrete Fourier Transform DFT X (! ) = 1 X n = 1 x [n ]e j !n The Scilab command 99K[xf ] = dft(x, ag); x is the time domain representation xf is the frequency domain representation ag = 1 or 1 Notice Cosine is Even Symmetric, hence this 64point DFT is real with peaks at 4 and 60 (644) Faster way t Iman Mukherjee Digital Signal Processing and Filter Design using Scilab Digital Signal Processing and Filter Design using Scilab Basic signal processing toolsDiscrete Fourier Transform DFT X (! ) = 1 X n = 1 x [n ]e j !n The Scilab command 99K[xf ] = dft(x, ag); x is the time domain representation xf is the frequency domain representation ag = 1 or 1 Notice Cosine is Even Symmetric, hence this 64point DFT is real with peaks at 4 and 60 (644) Faster way t Iman Mukherjee Digital Signal Processing and Filter Design using Scilab Digital Signal Processing and Filter Design using Scilab Basic signal processing toolsDiscrete Fourier Transform DFT X (! ) = 1 X n = 1 x [n ]e j !n The Scilab command 99K[xf ] = dft(x, ag); x is the time domain representation xf is the frequency domain representation ag = 1 or 1 Notice Cosine is Even Symmetric, hence this 64point DFT is real with peaks at 4 and 60 (644) Faster way t Iman Mukherjee Digital Signal Processing and Filter Design using Scilab Digital Signal Processing and Filter Design using Scilab Basic signal processing toolsDiscrete Fourier Transform DFT X (! ) = 1 X n = 1 x [n ]e j !n The Scilab command 99K[xf ] = dft(x, ag); x is the time domain representation xf is the frequency domain representation ag = 1 or 1 Notice Cosine is Even Symmetric, hence this 64point DFT is real with peaks at 4 and 60 (644) Faster way t Iman Mukherjee Digital Signal Processing and Filter Design using Scilab Digital Signal Processing and Filter Design using Scilab Basic signal processing toolsFast Fourier Transform FFT x= t(a ,1) or x= t(a) y= t2(x,n,m) twodimension x= t(a,1,dim,incr) multidimensional

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