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ee425matlab - EE425 Introduction to Matlab 1 What is MATLAB...

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ATLAB Matlab EE425 Fall 1997 Introduction to symbolic samples 1 What is M ? 2 About This Document Matlab Mat Lab Matlab fortran linpack eispack fortran Matlab Matlab Matlab Matlab Matlab Matlab Matlab Matlab Matlab Matlab Matlab Matlab The primary software tool we will be using in EE425 is a numerical linear algebra package called , which stands for rix oratory. was initially developed to be a user-friendly front end to the popular libraries and in the 1970s. Since that time, it has acquired an enormous user base in all fields of science and engineering by effectively removing the need for scientists to master the intricacies of a general purpose programming language such as C or . One of the main strengths of is its ability to handle vector and matrix data types in a natural way. In fact, vectors and matrices are the only types of ob- jects that understands. In this respect, differs significantly from software packages such as Maple and Mathematica. These systems are designed to do mathematics, whereas can only do numerical computation. For example, you could not compute the indefinite integral of a function in . It is not even clear how you would specify the function that you wished to integrate. However, you could obtain a numerical approximation to a definite integral by com- puting values of the function in question on a fine grid and using a rectangular or trapezoidal approximation. In the integration example above, the list of numbers representing the values of the function at regularly-spaced intervals can be thought of as a vector. In other words, instead of having a symbolic representation of the function, we have a vector of of the function. It is this aspect of the environment that makes it so useful in discrete-time signal processing. In DSP we generally do not work with the underlying continuous-time signal which gave rise to the vector of samples — we process the samples themselves. Since is optimized for vector operations, it is a natural choice for DSP. This document is designed to familiarize you with the basic use of in the signal processing lab. Although we have attempted to give you a reasonably complete introduction, we obviously cannot tell you everything there is to know about . We would therefore like to stress the importance of independent experimentation with the software. There is no substitute for playing around with yourself and trying out the examples in this tutorial. In the past, we have found that much of the time in the lab is spent on programming rather than investigation of the signal processing issues in the lab. By learning now, you will significantly reduce the amount of time you spend in the lab. 1
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- all ATLAB π j i π . π 3 Basic M 3.1 Scalar Arithmetic Matlab Matlab Matlab Matlab Matlab Matlab + - * / >> 3+4 ans = 7 >> 4/5 ans = 0.8000 >> (3.5 - 1/16) * 12 ans = 41.2500 pi j i >> pi ans = 3.1416 >> j ans = 0 + 1.0000i >> i ans = 0 + 1.0000i format long >> format long >> pi ans = 3.14159265358979 has all the standard scalar arithmetic operators: addition ( ), subtraction ( ), multiplication ( ), and division ( ). These are used in exactly the way you would expect. For example:
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