By Forester W. Isen

This e-book is quantity I of the sequence DSP for MATLAB™ and LabVIEW™. the complete sequence comprises 4 volumes that jointly conceal simple electronic sign processing in a realistic and available demeanour, yet which still comprise all crucial starting place arithmetic. because the sequence name implies, the scripts (of which there are greater than 2 hundred) defined within the textual content and provided in code shape (available at www.morganclaypool.com/page/isen) will run on either MATLAB and LabVIEW. quantity I comprises 4 chapters. the 1st bankruptcy supplies a quick evaluate of the sphere of electronic sign processing. this is often by means of a bankruptcy detailing many beneficial indications and ideas, together with convolution, recursion, distinction equations, LTI platforms, and so on. The 3rd bankruptcy covers conversion from the continual to discrete area and again (i.e., analog-to-digital and digital-to-analog conversion), aliasing, the Nyquist cost, normalized frequency, conversion from one pattern fee to a different, waveform iteration at a number of pattern premiums from saved wave info, and Mu-law compression. The fourth and ultimate bankruptcy of the current quantity introduces the reader to many very important ideas of sign processing, together with correlation, the correlation series, the true DFT, correlation via convolution, matched filtering, basic FIR filters, and straightforward IIR filters. bankruptcy four, specifically, offers an intuitive or "first precept" knowing of ways electronic filtering and frequency transforms paintings, getting ready the reader for Volumes II and III, which supply, respectively, exact assurance of discrete frequency transforms (including the Discrete Time Fourier remodel, the Discrete Fourier rework, and the z-Transform) and electronic filter out layout (FIR layout utilizing Windowing, Frequency Sampling, and optimal Equiripple options, and Classical IIR design). quantity IV, the end result of the sequence, is an introductory therapy of LMS Adaptive Filtering and functions. The textual content for all volumes includes many examples, and lots of valuable computational scripts, augmented by way of demonstration scripts and LabVIEW digital tools (VIs) that may be run to demonstrate numerous sign processing techniques graphically at the user's display screen. desk of Contents: an summary of DSP / Discrete indications and ideas / Sampling and Binary illustration / rework and Filtering rules

**Read Online or Download DSP for MATLAB and LabVIEW, Volume I: Fundamentals of Discrete Signal Processing (Synthesis Lectures on Signal Processing) PDF**

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**Additional info for DSP for MATLAB and LabVIEW, Volume I: Fundamentals of Discrete Signal Processing (Synthesis Lectures on Signal Processing)**

**Sample text**

8: (a) The ﬁrst three weighted harmonics of a square wave; (b) Superposition of the waves shown in (a). 4. USEFUL SIGNALS, SEQUENCES, AND CONCEPTS 19 index zero. For example, the sequence [1,2,3,4] that has corresponding sample indices [3,4,5,6], when folded, results in the sequence [4,3,2,1] and corresponding indices [-6,-5,-4,-3]. To illustrate the above ideas, we can, for example, let x[n] = [1,2,3,4] with corresponding sample indices n = [3,4,5,6], and compute x[−n] using MathScript. 9 EVEN AND ODD DECOMPOSITION Any real sequence can be decomposed into two components that display even and odd symmetry about the midpoint of the sequence.

Compute the response to the sequence x[n] = ones(1, 4) of the FIR represented by the difference equation given below (assume that x[n] = 0 for n < 0). 46 CHAPTER 2. DISCRETE SIGNALS AND CONCEPTS y[n] = x[n] − x[n − 1] The sequence of computation is from n = 0 forward in time: y[0] = x[0] - x[-1] = 1 y[1] = x[1] - x[0] = 1 - 1 = 0 y[2] = x[2] - x[1] = 1 - 1 = 0 y[3] = x[3] - x[2] = 1 - 1 = 0 y[4] = x[4] - x[3] = 0 -1 = -1 To do the above using MathScript, the following code is one possibility. The reader should study the code and be able to explain the purpose of or need for 1) extending x to a length of ﬁve by adding one zero-valued sample, 2) the statement y(1) = x(1), and 3) running n effectively from 1 to 5 rather than 0 to 4.

Demonstrate linearity and time invariance for the system below using MathScript. y[n] = 2x[n] We begin with code to compute y[n] = 2x[n] where x[n] can be scaled by the constant A. The code below generates a cosine of frequency F , scaled in amplitude by A as x[n], computes y[n], and then plots x[n] and y[n]. , if the input signal is scaled by A, so is the output signal (comparison of the results from running the two example calls given in the script above will demonstrate the scaling property).