Adaptive Colormap Function Creates a Colormap Specific to Data by Tristan Ursell

Easily design and fit a colormap to the values in your data! (color, red, blue)

slide_map=rgbslide(mat_in,varargin)

lms adaptive noise cancellation by jerin

Its like single perceptron neural network..:D (adaptive, noise, signal processing)

noisecancel.m

Adaptive Robust Numerical Differentiation by John D'Errico

Numerical derivative of an analytically supplied function, also gradient, Jacobian & Hessian (hessian, jacobian, gradient)

derivest_demo

multivariable_calc_demo

derivest(fun,x0,varargin)

Multi Channel Physiological Signal Estimation (PhysioNet 2010 Challenge entry) by Ikaro Silva

Algorithm using GALL and Kalman filters for channel estimation. (multi channel, adaptive, estimation)

[sig,varargout]=mcaf(x,varargin)

Fundamental Frequency Tracking through Comb (Notch) IIR Filtering by Ikaro Silva

Implements the algorithm described in IEEE Signal Processing Magazine (11/2009) by Tan and Jiang. (frequency tracking, harmonics, adaptive)

[varargout]=harmonic_est(x,varargin)

LqrSim by Giampiero Campa

Algebraic Riccati Equation solution in Simulink via C+Fortran (simulink, riccati, are)

demos

contents.m

sfcndemo_lqry

Iterative Adaptive Simpson and Lobatto Quadrature by Matthias Chung

Iterative Adaptive Simpson and Lobatto Quadrature (integration, adaptive, simpson)

adaptiveLobatto(fcn, a, b, varargin)

adaptiveSimpson(fcn, a, b, varargin)

cumquad by Adam Wyatt

Cumulative integration of analytical functions via adaptive simpsons quadrature. (integration, cumulative integratio..., adaptive)

cumquad(funfcn,a,b,tol,trace,varargin)

2D adaptive residual subsampling for Radial Basis Functions by Alfa Heryudono

This program solves initial-boundary value problems particularly 2D Burgers' equation adaptively (burgers, differential equation..., rbf)

Jburgers(t,u,epsilon,Dx,Dy,Dxx,Dyy)

burgers(t,u,epsilon,Dx,Dy,Dxx,Dyy)

coarserefine2d(f,intrv,theta,n,topc)

Ramdomic Search by Giovani Tonel

Unconstrained global optimization using adaptive random search. (optimization, ramdomic, search)

[xo,Ot,nS]=buscarnd(S,x0,ip,nOt,samples,Lb,Ub,problem,tol,m...

COMPUTER ADAPTIVE TEST DEMYSTIFIED (GRE PATTERN) by Divakar Roy

Demystifies how a computer adaptive test is created (adaptive, test, gre)

[ans_arr,next_lin_num,q_time]=ask_rc_full(input_text_file_n...

[ans_array,time_arr]=final_test

[ans_com,q_time]=ask_rc2_long(input_text_file_name,start_li...

Adaptive residual subsampling for Radial Basis Functions by Alfa Heryudono

This simple codes solve initial-boundary value problems particularly Burgers' equation adaptively (differential equation..., radial basis function..., rbfs)

Jburgers(t,u,epsilon,D1,D2)

burgers(t,u,epsilon,D1,D2)

burgersplot(t,y,flag,varargin,x,han)

FRAME MAKER + ADAPTIVE FRAMING by Divakar Roy

Use your own images to make picture frames (enhancement, adaptive, border)

adpframe

Adaptive-degree polynomial (Savitzky-Golay) filter for data differentiation by Jianwen Luo

Adaptive-degree polynomial filter (Savitzky-Golay Filter) for data differentiation (1st derivative). (filter design, filter analysis, savitzkygolay)

polynomial_degree=adpf_diff(data_frame)

Pkmi_Calculate.m

Adaptive-Degree Polynomial Filter (Savitzky-Golay Filter) by Jianwen Luo

Obtain the polynomial degree selected in the adaptive-degree polynomial filter. (filter design, filter analysis, savitzkygolay filter)

h=sgsdf_smooth_closed_form(p,m)

hnstm=sgsdf_gram_poly_closed_form(n,s,t,m)

polynomial_degree=adpf(data_frame)

Art1-FuzzyArt-Artmap-FuzzyArtmap by Bernabe Linares-Barranco

MATLAB routines for Art1, Artmap, Fuzzy Art, Fuzzy Artmap (artmap, fuzzy art, neural and fuzzy syst...)

Robust Adaptive Control by Petros Ioannou

Companion Software (companion software, control, adaptive)

C-Adaptive Equalizer by Muhammad Mumtaz Khokhar

Complex adaptive equalizer. (communications, adaptive, complex)

LMS_Equalizer.m

art1s.zip by Val Ninov

Adaptive Resonance Theory (ART) Neural Network (adaptive, fuzzy logic, neural networks)

art1s(p,rho,flag,V,W)

letno(noise)

letplot(p,r,c)