MATLAB Optimization Techniques by Cesar Lopez

By Cesar Lopez

MATLAB is a high-level language and surroundings for numerical computation, visualization, and programming. utilizing MATLAB, you could study info, strengthen algorithms, and create versions and functions. The language, instruments, and integrated math services make it easier to discover a number of techniques and achieve an answer swifter than with spreadsheets or conventional programming languages, comparable to C/C++ or Java.

MATLAB Optimization strategies introduces you to the MATLAB language with sensible hands-on directions and effects, permitting you to quick in achieving your objectives. It starts via introducing the MATLAB atmosphere and the constitution of MATLAB programming earlier than relocating directly to the maths of optimization. The important a part of the booklet is devoted to MATLAB’s Optimization Toolbox, which implements cutting-edge algorithms for fixing multiobjective difficulties, non-linear minimization with boundary stipulations and regulations, minimax optimization, semi-infinitely restricted minimization and linear and quadratic programming. quite a lot of routines and examples are incorporated, illustrating the main standard optimization tools.

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Gmres(A,b,tol) Solves Ax = b by specifying tolerance. gmres(A,b,tol,maxit) Solves Ax = b by specifying the tolerance and the maximum number of iterations. gmres(A,b,tol,maxit,M) Solves the system inv(M) * A * x = inv (M) * b. gmres(A,b,tol,maxit,M1,M2) Solves the system inv(M) * A * x = inv (M) * b with M = M1 * M2. gmres(A,b,tol,maxit,M1,M2,x0) Solves the system inv(M) * A * x = inv (M) * b with M = M1 * M2 and initial value x0. [x,f] = gmres(A,b,…) Tries to solve the system and returns a convergence indicator f (0 = convergence, 1 = no-convergence, 2 = ill-convergence, 3 = stagnation and 4 = very extreme numbers).

N=1 % The inverse DFT (computed by IFFT) is given by % N % x(n) = (1/N) sum X(k)*exp( j*2*pi*(k-1)*(n-1)/N), 1 <= n <= N. % k=1 % % See also IFFT, FFT2, IFFT2, FFTSHIFT. info Chapter 2 ■ MATLAB Programming TRY... CATCH The instructions between try and catch are executed until an error occurs. The instruction lasterr is used to show the cause of the error. , instruction end RETURN The return statement terminates the current script and returns the control to the invoked function or the keyboard.

6 Flow Control: FOR, WHILE and IF ELSEIF Loops The use of recursive functions, conditional operations and piecewise defined functions is very common in mathematics. The handling of loops is necessary for the definition of these types of functions. Naturally, the definition of the functions will be made via M-files. FOR Loops MATLAB has its own version of the DO statement (defined in the syntax of most programming languages). This statement allows you to run a command or group of commands repeatedly.

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