Deep Learning Data preparation, design, simulation, and deployment for deep neural networks Image Processing and Computer Vision Acquire, process, and analyze images and video for algorithm development and syste
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from...
3Citations Abstract We present a matrix language compiler CMC which translates annotated MATLAB scripts into Fortran 90 programs. Distinguishing features of CMC include its applicability to programs with sparse matrix computations and its capability of source-level optimization in MATLAB language. Different...
Matrix);%另一种可以控制格式的写出fid=fopen('test.txt','w');formatSpec='%d\t';fori=1:NumN...
Input matrix. Data Types:single|double|int8|int16|int32|int64|uint8|uint16|uint32|uint64|logical|char Complex Number Support:Yes Diagonals to include, specified as a scalar.k = 0is the main diagonal,k > 0is above the main diagonal, andk < 0is below the main diagonal. ...
function crc_code=func_crc_encode(signal,k,n,r,G); %信号长度 Flen = length(signal); %将信号按每帧的编码程度分组 signal_team= reshape(signal,Flen/k,k); %编码矩阵 code_matrix= zeros(Flen/k,n); for i = 1:Flen/k a = zeros(1,k); ...
double b,c; plhs[0]=mxCreateDoubleMatrix(1,1,mxREAL); a=mxGetPr(plhs[0]);// b=*(mxGetPr(prhs[0])); c=*(mxGetPr(prhs[1])); *a=calculate(b,c); } \end{lstlisting} \begin{lstlisting}[language=c++, linewidth=\linewidth,caption={Draw the contrast curve and main interface code(...
Input array, specified as a matrix or array. For most norm types,Xmust be a matrix. However, forFrobenius normcalculations,Xcan be an array. Data Types:single|double Complex Number Support:Yes Norm type, specified as2(default), a positive real scalar,Inf, or-Inf. The valid values ofpand...
(nely+1)]); alldofs = [1:2*(nely+1)*(nelx+1)]; freedofs = setdiff(alldofs,fixeddofs); % SOLVING U(freedofs,:) = K(freedofs,freedofs) \ F(freedofs,:); U(fixeddofs,:)= 0; %%%%%%%%%% ELEMENT STIFFNESS MATRIX %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function...
Fixed-point code generation does not support tables or categorical arrays. So, define the predictor data using a numeric matrix, and define the class labels using a logical vector. A logical vector uses memory most efficiently in a binary classification problem. Get X = table2array(tbl); Y...