代码搜索:optimisation

找到约 403 项符合「optimisation」的源代码

代码结果 403
www.eeworm.com/read/430025/8772286

asv optim.asv

%Explanation:Optimisation of the driving signal for a general Z matrix %output network given the best choice of driving signals in terms of %efficiency. %Function [I1,I2]=optim(Z,I1max,I2max,Vdd,Zl
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c cdotc.c

#include "f2c.h" #include "netlib.h" /* Modified by Peter Vanroose, June 2001: manual optimisation and clean-up */ /* Complex */ void cdotc_( ret_val, n, cx, incx, cy, incy) complex *ret_val;
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h newmatnl.h

//$$ newmatnl.h definition file for non-linear optimisation // Copyright (C) 1993,4,5: R B Davies #ifndef NEWMATNL_LIB #define NEWMATNL_LIB 0 #include "newmat.h" #ifdef use_namespace nam
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h newmatnl.h

//$$ newmatnl.h definition file for non-linear optimisation // Copyright (C) 1993,4,5: R B Davies #ifndef NEWMATNL_LIB #define NEWMATNL_LIB 0 #include "newmat.h" #ifdef use_namespace nam
www.eeworm.com/read/100394/15874948

h newmatnl.h

//$$ newmatnl.h definition file for non-linear optimisation // Copyright (C) 1993,4,5: R B Davies #ifndef NEWMATNL_LIB #define NEWMATNL_LIB 0 #include "newmat.h" #ifdef use_namespace nam
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cpp newmatnl.cpp

//$$ newmatnl.cpp Non-linear optimisation // Copyright (C) 1993,4,5,6: R B Davies #define WANT_MATH #define WANT_STREAM #include "newmatap.h" #include "newmatnl.h" #ifdef use_n
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cpp newmatnl.cpp

//$$ newmatnl.cpp Non-linear optimisation // Copyright (C) 1993,4,5,6: R B Davies #define WANT_MATH #define WANT_STREAM #include "newmatap.h" #include "newmatnl.h" #ifdef use_namespace na
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cpp newmatnl.cpp

//$$ newmatnl.cpp Non-linear optimisation // Copyright (C) 1993,4,5,6: R B Davies #define WANT_MATH #define WANT_STREAM #include "newmatap.h" #include "newmatnl.h" #ifdef use_namespace na
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cpp newmatnl.cpp

//$$ newmatnl.cpp Non-linear optimisation // Copyright (C) 1993,4,5,6: R B Davies #define WANT_MATH #define WANT_STREAM #include "newmatap.h" #include "newmatnl.h" #ifdef use_namespace na
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htm demolgd1.htm

Netlab Reference Manual demolgd1 demolgd1 Purpose Demonstrate simple MLP optimisation with on-line gradient descent Synopsi