Neural Network Based System Identification
نویسنده
چکیده
u(t−1) u(t−2) y(t−1) y(t−2) y(t) This note contains important information on how the present toolbox is to be installed and the conditions under which it may be used. Please read it carefully before use. The note should be sufficient for being able to make the essential portion of the toolbox functions work properly. However, to enhance performance a number of functions have been rewritten in C and in order to compile these, it is necessary to read the information about CMEX files found in the Matlab External Interface Guide as well as to have some familiarity with compiling C programs. NEW IN VERSION 1.1 A few bugs have been fixed and the following six functions have been included in the new version igls: Iterated generalized least squares training of multi-output networks nnarxm: Identify a multi-output neural network ARX (or AR) model. nnigls: Iterated generalized LS training of multi-output NNARX models kpredict: k-step ahead prediction of the network output. nnloo: Leave-One-Out estimate of generalization error for NNARX models xcorrel: High-order cross-correlation functions. INSTALLING THE TOOLBOX ° The toolbox is provided in two versions. One for MATLAB 4.2 an one for MATLAB 5. Both versions have been tested under UNIX on a HP9000/735 and MATLAB 4.2c.1 for WINDOWS 3.1/95 on an IBM compatible PENTIUM. ° Due to a bug in the " fprintf " function in MATLAB 4.2 for MS-Windows, many of the functions will generate a very inconvenient output in the MATLAB command window. If this is to be avoided, replace " \r " in the line: fprintf('iteration # %i PI = %4.3\r',iteration-1,PI); with " \n " in the m-files batbp, incbp, marq, marq2, marqlm, nnarmax1, nnarmax2, nniol, nnoe, nnssif, nnrarmx1, mmrarmx2, rpe. (it is always close to line 10 from the bottom). The problems should have been corrected in version 5. On UNIX systems there should not be any such problems (it is also thought that the toolbox can be used on Macintosh computers). ° The signal processing toolbox is required by the validation functions (nneval, nnvalid, ifvalid) to compute the correlation functions. Otherwise no additional toolboxes should be necessary. ° All toolbox functions are implemented as plain m-files, but to enhance performance CMEX duplicates have been written for some of the most important functions. In the MATLAB 4.2 version the Makefile contains the commands necessary for compiling the C-routines. If one is running MATLAB under HP-UX, it should be …
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