# Benchmarking sudoku solvers in matlab

The following Matlab project contains the source code and Matlab examples used for benchmarking sudoku solvers.
There are more than 20 Sudoku solvers submitted in File Exchange.

The following Matlab project contains the source code and Matlab examples used for analysis and solution of discrete ill-posed problems. .
Regularization Tools: A MATLAB package for Analysis and Solution of Discrete Ill-Posed Problems.

The following Matlab project contains the source code and Matlab examples used for fixed point atan2 using cordic.
This demo consists of a m-file script (fixed_point_atan2_using_cordic.

The following Matlab project contains the source code and Matlab examples used for gauss seidel load flow analysis.
1.

The following Matlab project contains the source code and Matlab examples used for sqrt(x^2 + y^2) and atan(y x) via cordic.
Calculation of sqrt (x^2 + y^2) and atan (y/x) via the CORDIC algorithm.
This function perform 9 iterations

The following Matlab project contains the source code and Matlab examples used for cos and sin via cordic.
Input: A angle (theta) between 0 and 360 degrees.
Output:
cos(theta)
sin(theta)

The following Matlab project contains the source code and Matlab examples used for routh hurwitz criteria using user defined function.
RA=ROUTH(R,EPSILON) returns the symbolic Routh array RA for polynomial.

The following Matlab project contains the source code and Matlab examples used for opensees pre and post processing.
This toolbox provdies pre- and post- processing functionalities for the some OpenSees tcl file.

The following Matlab project contains the source code and Matlab examples used for munkres assignment algorithm.
Munkres algorithm (also known as Hungarian algorithm) is an efficient algorithm to solve the assignment problem in polynomial-time.

The following Matlab project contains the source code and Matlab examples used for convert covariance matrix to correlation matrix.
The function is "remix" of native matlab cov2corr() function, which produces correlation matrix with elements on its main diagonal slightly greater or less then 1.

The following Matlab project contains the source code and Matlab examples used for pareto front.
Identifying the Pareto Front from a set of points in a multi-objective space is the most important and also the most time-consuming task in multi-objective optimization.

The following Matlab project contains the source code and Matlab examples used for adaptive algorithm for linear parabolic problems for 2d polygonal domain.
Solves FEM analogue to parabolic equation:
d/dt(u)-div(D(x,t)u) +C*Nabla(u)+R*u= f(x,t) u=u(x,t) scalar fct
u(x,t) = u_d(t) on Dirichlet-edge
D(x,t)*Nabla(u)*n(x) = g(x,t) on Neumann-edge.

The following Matlab project contains the source code and Matlab examples used for spok checks if a matlab sparse matrix is ok.
This function is very helpful for authors of mexFunctions that return sparse matrices to MATLAB.

The following Matlab project contains the source code and Matlab examples used for discrete-time periodic riccati equation solver for periodic lq state-feedback design .
The m-file "dpre" solves the discrete-time periodic optimal control problem by a cyclic QZ method.

The following Matlab project contains the source code and Matlab examples used for weighted least squares + weighted min max optimization.
This is a wrapper function to solve optimization problems (using FMINCON) of the form:
min w.

The following Matlab project contains the source code and Matlab examples used for adaptive form of gaussleg.m. .
gaussquad(f,a,b)
GAUSSQUAD uses an adaptive formulation of Gauss-Legendre quadrature to evaluate the integral of f from a to b with default tolerance of 10^-14.

The following Matlab project contains the source code and Matlab examples used for solves multiple phase optimal control problems. .
Gauss Pseudospectral Optimization Software(GPOPS) is a MATLAB program for solving non-sequential multiple-phase optimal control problems.

The following Matlab project contains the source code and Matlab examples used for quadratic programming control allocation toolbox .
The Quadratic Programming Control Allocation Toolbox (QCAT) provides MATLAB implementations of a number of algorithms for control allocation based on quadratic programming.

The following Matlab project contains the source code and Matlab examples used for analytical solution for orthogonal linear least squares in two dimensions.
ORTHLLS2D returns the Orthogonal Linear Least Squares estimate for parameters of line a x + b y + c = 0
function f = OrthLLS2D(x, y)
Inputs x and y must be real vectors of equal size.

The following Matlab project contains the source code and Matlab examples used for thin plate splines.
Features:
(1) support arbitrary control points
(2) allow regularization
(3) estimate the warp parameters from corresponding pairs

The following Matlab project contains the source code and Matlab examples used for finds the roots of a set of nonlinear equations .
derives number of dimensions ( variables ) of given set of function
( class - inline , symbolic or char ) then finds the roots of a set (
nonlinear equations ) Example: F = inline ( '[ ( x ^ 2 ) + ( x * y ) - 10 ; y + ( 3 * ( x * ( y ^ 2 ) ) ) - 57 ]' ) ;
smartnonlinrgen ( F ,[ 1 ; 1 ] , [ 2 ; 2 ] , 100 )
ans =
2.

The following Matlab project contains the source code and Matlab examples used for calculation of pareto points.
A point X* is said to be Pareto optimal one if there is no X such that Fi(X)<=Fi(X*) for all i=1...n, with at least one strict inequality.
These points are also known as non-dominated, non-inferior, or efficient points.

The following Matlab project contains the source code and Matlab examples used for bidirectional branch and bound minimum singular value solver (v2).
B3MSV Bidirectional Branch and Bound(B3) subset selection using the the Minimum Singular Value (MSV) as the criterion.

The following Matlab project contains the source code and Matlab examples used for subsref2 often faster than subsref for c=a(i,j) when a is sparse.
subsref2 uses sparse matrix multiplication to compute C=A(i,j).

The following Matlab project contains the source code and Matlab examples used for coin and dice.
Compute the estimated average number of coin tosses (or dice throws) to get a given sequence of Heads-and-Tails (or a sequence of intergers ranging from 1 to 6)
The inputs are:
- The Sequence (row vector)
- The Number of Monte-Carlo Simulations
The outputs are the estimated (Monte-Carlo) expectation of number of tosses/throws to get the input sequence, along with the standard deviation of the error (due to the randomness of the simulation).

The following Matlab project contains the source code and Matlab examples used for vebyk performs ordinary kriging and can be easily adapted to other kriging methods. .
The program is designed to interpolate values on a regular two-dimensional grid using ordinary kriging.

The following Matlab project contains the source code and Matlab examples used for orthonormalization relative to matrix a .
ORTHA Orthonormalization Relative to matrix A
Q=ortha(A,X)
Q=ortha('Afunc',X)
computes an orthonormal basis Q for the range of X, relative to the scalar product using a positive definite and selfadjoint matrix A.

The following Matlab project contains the source code and Matlab examples used for finds the root(s) of a function of one variable, including complex roots, using newton's method. .
NEWTZERO(f,xr,n,tol) finds roots of function f near guess xr with n iterations to tolerance tol.

The following Matlab project contains the source code and Matlab examples used for generalized orthogonalization.
Input:
A: (m x n) matrix
B: (m x m) matrix, symmetric positive-definite
Output:
Q : (m x k), where k is the rank of A
span<Q> = span<A> the columns of Q span the same space as the
columns of A, and the number of columns of Q is the rank of A.

The following Matlab project contains the source code and Matlab examples used for generalized newton raphson method.
Two methods are provided -
1) an automatic updation method which can be effectively used outside of a loop since it writes out a newton-raphson computation file from the parameters received.

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