# Dos kernel in c

The following C project contains the C source code and C examples used for dos kernel. The essential part of the operating system, responsible for resource allocation, low-level hardware interfaces, security etc.

The following Matlab project contains the source code and Matlab examples used for kernel density estimation of 2 dim with sj bandwidth.
2 dimenstion Kernel density Estimation with Sheater Jones bandwidth for each variable.
Also the Sheater Jones bandwidth selection
method will work for the univariate.

The following Matlab project contains the source code and Matlab examples used for adaptive optimal kernel.
A time-frequency representation which uses a signal-dependent, radially Gaussian kernel that adapts over time.

The following Matlab project contains the source code and Matlab examples used for rotating kernel transformation (lee & rhodes).
The Rotating Kernel Transformation convolves an image with several orientations of a kernel.

The following Matlab project contains the source code and Matlab examples used for efficient kernel smoothing regression using kd tree.
Kernel regression is a power full tool for smoothing, image and signal processing, etc.

The following Matlab project contains the source code and Matlab examples used for kernel smoothing regression.
Non-parametric regression is widely used in many scientific and engineering areas, such as image processing and pattern recognition.

The following Matlab project contains the source code and Matlab examples used for conditional nonparametric kernel density.
Ref: Sharma A 2000 J. of Hydrology (Part3-nonparametric probablistic forecast model)

The following Matlab project contains the source code and Matlab examples used for kernel density estimation.
% fast and accurate state-of-the-art
% bivariate kernel density estimator
% with diagonal bandwidth matrix.

The following Matlab project contains the source code and Matlab examples used for kernel ridge regression.
The Gaussian Kernel can be changed to any desired kernel. However such a change will not dramatically improve results. This is a variant of ridge regression using the kernel trick (Mercers Theorem).

The following Matlab project contains the source code and Matlab examples used for multivariate gaussian kernel in any derivative order.
NDGAUSS: create ND gaussian kernel in any derivative order.

The following Matlab project contains the source code and Matlab examples used for kernel decomposition.
This function does the decomposition of a separable nD kernel into
its 1D components, such that a convolution with each of these
components yields the same result as a convolution with the full nD
kernel, at a drastic reduction in computational cost.

The following Matlab project contains the source code and Matlab examples used for separate kernel in 1d kernels.
This function SEPARATEKERNEL will separate ( do decomposition of ) any
2D, 3D or nD kernel into 1D kernels.

The following Matlab project contains the source code and Matlab examples used for kernel density estimator.
% Reliable and extremely fast kernel density estimator for one-dimensional data;
% Gaussian kernel is assumed and the bandwidth is chosen automatically;
% Unlike many other implementations, this one is immune to problems
% caused by multimodal densities with widely separated modes (see example).

The following Matlab project contains the source code and Matlab examples used for on the kernel function selection of nonlocal filtering for image denoising.
MATLAB implementation of the paper J. Tian, W. Yu and S. Xie,
"On The Kernel Function Selection Of Nonlocal Filtering For Image Denoising," Proc. Int. Conf. on Machine Learning and Cybernetics, pp. 2964-2969, Jul. 2008, Kunming, China.

The following Matlab project contains the source code and Matlab examples used for kernel discriminant analysis .
Examples:
%
% fea = rand(50,70);
% gnd = [ones(10,1);ones(15,1)*2;ones(10,1)*3;ones(15,1)*4];
% options.

The following Matlab project contains the source code and Matlab examples used for blackjack computational kernel.
Calculates the profit and loss when playing a single hand of blackjack

The following Matlab project contains the source code and Matlab examples used for bivariant kernel density estimation (v2.1).
This function implements bivariant Gaussian kernel density estimation.

The following Matlab project contains the source code and Matlab examples used for bivariate kernel density and regression.
Returns, for two data series:
Marginal kernel densities
Bivariate kernel density
Conditional kernel density
Nadaraya-Watson kernel regression
kernel quantile regression
Method: Gaussian kernel, Silverman rule

The following Matlab project contains the source code and Matlab examples used for bivariate kernel regression with restrictions.
bivkernrest returns the marginal kernel densities of the two input data series, the bivariate kernel density, the conditional kernel densities, and the conditional expectations.

The following Matlab project contains the source code and Matlab examples used for locally adaptive kernel density estimation.
First thing to do:
Run a tutorial code, tutorial.

The following Matlab project contains the source code and Matlab examples used for kernel density estimation.
** Please also check ssvkernel.

The following Matlab project contains the source code and Matlab examples used for violin plot based on kernel density estimation.
This function creates simple violin plots by estimating the kernel density, using matlabs default ksdensity().

The following Matlab project contains the source code and Matlab examples used for kernel density estimation for circular functions.
See also http://dylan-muir.

The following Matlab project contains the source code and Matlab examples used for fast moving average.
In terms of behavior, this is an alternative to filter() for a moving-average kernel.

The following Matlab project contains the source code and Matlab examples used for multi dimensional kernel density estimates over periodic domains.
See also http://dylan-muir.

The following Matlab project contains the source code and Matlab examples used for fast kernel density estimator (multivariate).
The code implements an approximation of the multivariate bandwidth calculation from [1].

The following Matlab project contains the source code and Matlab examples used for find optimal kernel.
%function k=FindOptKern(InSig,OutSig,MaxnLags)
%
% Given InSig, OutSig, and the MaxnLags, this will find the optimal causal
% kernal of length MaxnLags that when convolved with InSig gives the
% optimal approximation to OutSig in a least squares sense.

The following Matlab project contains the source code and Matlab examples used for kernel wiener filter (kernel dependency estimation).
The kernel Wiener Filter (kernel Dependency Estimation) in MATLAB.

The following Matlab project contains the source code and Matlab examples used for kernel k means.
This function performs kernel version of kmeans algorithm.