Magnitude - SCILAB

1 SignalProcessingWithScilabScilabGroup-11 0010110210310-160-150-140-130-120-110-10 0-90 Magnitude Hz db -110010110210310-180-900 Phase Hz degrees -->a=-2* %p i; b= 1; c= 18 *% pi ;d =1 ;-->sl=sy sl in (' c' ,a ,b ,c ,d );-->bode( sl.)

2 1, 10 0) ;-->s=pol y( 0, 's ') ;-->S1=s+ 2* %p i* (1 5+ 10 0* %i );-->S2=s+ 2* %p i* (1 5- 10 0* %i ).

3 -->h1=1/ re al (S 1* S2 )h1=1-------- -- -- -- -- -- -- -- -- 2+

4 6s+s-->h1=sy sl in (' c' ,h 1) ;-->bode( h1 ,1 0, 10 00.)

5 01 );-->h2=ss 2t f( sl );-->bode( h1 *h 2, .1 ,1 00 0, .0 1) ;SIGNALPROCESSINGWITHSCILABS cilab GroupINRIA Meta2 Project/ENPC CergreneINRIA - Unit e de recherche de Rocquencourt - Projet Meta2 Domaine de Voluceau - Rocquencourt - 105 - 78153 Le Chesnay Cedex (France)E-mail : document is an updated version of a primary work by Carey Bunks, Franc ois Delebecque, GeorgesLe Vey and Serge SteerContents1 Description of the Basic , Loading, Reading, and Writing of Random and System Transfer of of Transfer Space System Continuous of Development of Signal Processing 192 Representation of and Group.

6 SCILAB Code Used to Generate and and DFT and the Using of Chirp the 59iii3 FIR of to Sampling Remez Using the 814 IIR of IIR Filters From Analog of Analog of the of the of Low Pass Low Pass to Use the Implementation of Digital IIR Spectral of Power Modified Periodogram Using Correlation Using the Maximum Entropy Maximum Entropy Spectral Levinson to to Optimal Filtering and Kalman Statistics of a Gaussian Random Systems and Gaussian Random Estimation of Gaussian Random Kalman Filter Properties of the Kalman to Use the Example Using to Use the Using Square Root Kalman Householder to Use the Wiener to Use the Optimization in filter IIR Lp FIR Stochastic Factorization via state-space Filter the of the matrices H F of the Levinson Time-Frequency representations of Wigner spectral 1 Description of the Basic IntroductionThe purpose of this document is to illustrate the use of the SCILAB software package in a signal processingcontext.

7 We have gathered a collection of signal processing algorithms which have been implemented asScilab manual is in part a pedagogical tool concerning the study of signal processing and in part a practicalguide to using the signal processing tools available in SCILAB . For those who are already well versed in thestudy of signal processing the tutorial parts of the manual will be of less each signal processing tool available in the signal processing toolbox there is a tutorial section inthe manual explaining the methodology behind the technique. This section is followed by a section whichdescribes the use of a function designed to accomplish the signal processing described in the preceding sec-tions. At this point the reader is encouraged to launch a SCILAB session and to consult the on-line help relatedto the function in order to get the precise and complete description (syntax, description of its functionality,examples and related functions).

8 This section is in turn followed by an examples section demonstrating theuse of the function. In general, the example section illustrates more clearly than the syntax section how touse the different modes of the this manual thetypewriter-facefont is used to indicate either a function name or an exampledialogue which occurs in signal processing subject is illustrated by examples and figures which were demonstrated usingScilab. To further assist the user, there exists for each example and figure an executable file which recreatesthe example or figure. To execute an example or figure one uses the following SCILAB command-->exec( )which causes SCILAB to execute all the SCILAB commands contained in the file know what signal processing tools are available in SCILAB one would type-->disp(siglib)which produces a list of all the signal processing functions available in the signal processing SignalsFor signal processing the first point to know is how to load and save signals or only small portions of lengthysignals that are to be used or are to be generated by SCILAB .

9 Finally, the generation of synthetic (random)signals is an important tool in the development in implementation of signal processing tools. This sectionaddresses all of these Saving, Loading, Reading, and Writing FilesSignals and variables which have been processed or created in the SCILAB environment can be saved in fileswritten directly by SCILAB . The syntax for thesaveprimitive is-->save(file_name[,var_list])wherefile nameis the file to be written to andvarlistis the list of variables to be written. Theinverse to the operationsaveis accomplished by the primitiveloadwhich has the syntax-->load(file_name[,var_list])where the argument list is identical that used the commandssaveandloadare convenient, one has much more control over the transferof data between files and SCILAB by using the commandsreadandwrite. These two commands worksimilarly to the read and write commands found in Fortran.

10 The syntax of these two commands is as syntax forwriteis-->write(file,x[,form])The second argument,x, is a matrix of values which are to be written to the syntax forreadis-->x=read(file,m,n[,form])The argumentsmandnare the row and column dimensions of the resulting data the format specification order to illustrate the use of the on-line help for reading this manual we give the result of the Scilabcommand-->help readread(1) SCILAB Function read(1)NAME read - matrices readCALLING SEQUENCE[x]=read(file-name,m,n,[format]) [x]=read(file-name,m,n,k,format)PARAMETE RS file-name : string or integer (logical unit number)m, n : integers (dimensions of the matrix x). Set m=-1 if you dontknow the numbers of rows, so the whole file is : string (fortran format). If format= (a) then read reads a vec-tor of strings n must be equal to : integerDESCRIPTION reads row after row the mxn matrix x (n=1 for character chain) in the filefile-name (string or integer).