MATLAB的SVM算法實現，Matlab Support Vector Machine Toolbox，This toolbox was designed as a teaching aid, which matlab is
particularly good for since source code is relatively legible and
simple to modify. However, it is still reasonably fast if used
with the supplied optimiser. However, if you really want to speed
things up you should consider compiling the matrix composition
routine for H into a mex function. Then again if you really want
to speed things up you probably shouldn t be using matlab
anyway... Get hold of a dedicated C program once you understand
the algorithm.
This book is the product of a twenty-year resarch project at Rice University
to develop fundamental compiler technologies for Vector and parallel
computer systems. The effort was by Randy Allen and Ken Kennedy with the help of David Kuck and Michael Wolfe.
The DSPLIB is a collection of 39 high-level optimized DSP functions for the TMS320C64x device. This source code library includes C-callable functions (ANSI-C language compatible) for general signal processing math and Vector functions.
The DSPLIB is a collection of 39 high-level optimized DSP functions for the TMS320C64x device. This source code library includes C-callable functions (ANSI-C language compatible) for general signal processing math and Vector functions.
Will perform 3D Gaussian quadrature over a user-defined volume. The volume is defined by the user with function definitions entered in the appropriate spaces provided on the GUI. The user can change the number of Gauss points to use.
Function inputs need not accept Vector args.
16點FFT VHDL源程序，The xFFT16 fast Fourier transform (FFT) Core computes a 16-point complex FFT. The input data
is a Vector of 16 complex values represented as 16-bit 2’s complement numbers – 16-bits for
each of the real and imaginary component of a datum.
These instances, whenmapped to an N-dimensional space, represent a core set that can be
used to construct an approximation to theminimumenclosing ball. Solving the SVMlearning
problem on these core sets can produce a good approximation solution in very fast speed.
For example, the core-Vector machine [81] thus produced can learn an SVM for millions of
data in seconds.
The ISD51_Demo project for the MSC1200 shows how to use the ISD51
In-System-Debugger with flash breakpoints or hardware breakpoints.
By default, it is configured for flash breakpoints which allow you
to set real-time breakpoints in your software. Using Flash breakpoints
has also the benefit that no special handing for the shared interrupt
Vector is required, since the hardware break registers of the MSC1200
are not used at all.
