代码搜索：Generalized

找到约 2,645 项符合「Generalized」的源代码

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in gqr.in

GQR: Data file for testing Generalized QR and RQ routines 3 Number of values of M, P and N 0 3 10 Values of M 0 5 20 Valu
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m maxeig.m

%MAXEIG Maximum eigenvalue and the corresponding eigenvector. % [L, Q] = MAXEIG(A) returns the maximum eigenvalue L and the % corresponding eigenvector Q of the square matrix A. Maximum is % in the s
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m hinfcontrol.m

%This script is to illustrate how one can design H-infinity controllers in %Matlab. The example shows some different ways to synthesize a controller %for the mixed S/KS weighted sensitivity problem.
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m demglm1.m

%DEMGLM1 Demonstrate simple classification using a generalized linear model. % % Description % The problem consists of a two dimensional input matrix DATA and a % vector of classifications T. The da
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m demglm1.m

%DEMGLM1 Demonstrate simple classification using a generalized linear model. % % Description % The problem consists of a two dimensional input matrix DATA and a % vector of classifications T. The da
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m demglm1.m

%DEMGLM1 Demonstrate simple classification using a generalized linear model. % % Description % The problem consists of a two dimensional input matrix DATA and a % vector of classifications T. Th
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m demglm1.m

%DEMGLM1 Demonstrate simple classification using a generalized linear model. % % Description % The problem consists of a two dimensional input matrix DATA and a % vector of classifications T. Th
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m demglm1.m

%DEMGLM1 Demonstrate simple classification using a generalized linear model. % % Description % The problem consists of a two dimensional input matrix DATA and a % vector of classifications T. The da
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m demglm1.m

%DEMGLM1 Demonstrate simple classification using a generalized linear model. % % Description % The problem consists of a two dimensional input matrix DATA and a % vector of classifications T. Th
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m demglm1.m

%DEMGLM1 Demonstrate simple classification using a generalized linear model. % % Description % The problem consists of a two dimensional input matrix DATA and a % vector of classifications T. Th
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