代码搜索：vectors
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www.eeworm.com/read/252898/12256911
s startup.s
#
# *** Startup Code (executed after Reset) ***
#
#include "config.h"
# Standard definitions of Mode bits and Interrupt (I & F) flags in PSRs
.equ Mode_USR, 0x10
.
www.eeworm.com/read/150760/12265928
m rspoly2.m
function red_model = rspoly2(model,max_nsv)
% RSPOLY2 Reduced set method for second order homogeneous polynomial kernel.
%
% Synopsis:
% red_model = rspoly2(model)
% red_model = rspoly2(model,max_ns
www.eeworm.com/read/150760/12266160
m fld.m
function model = fld(data)
% FLD Fisher Linear Discriminat.
%
% Synopsis:
% model = fld(data)
%
% Description:
% This function computes the binary linear classifier based
% on the Fisher Linear Dis
www.eeworm.com/read/150760/12266164
m~ fld.m~
function model = fld(data)
% FLD Fisher Linear Discriminat.
%
% Synopsis:
% model = fld( data )
%
% Description:
% This function computes the binary linear classifier based
% on the Fisher Linear D
www.eeworm.com/read/149950/12329614
h clustering.h
#ifndef __CLUSTERING_H__
#define __CLUSTERING_H__
struct VQ_VECTOR
{
double* Data; //Input vector
int nDimension; //Dimension of input vector
int nCluster; //Class the vector belong
www.eeworm.com/read/251598/12331252
cmd test.cmd
/* Restrictions : The memory definitions MUST be preserved: VECTORS, XFER, SCRATCH, XFERHDR
and FIFO. FIFO is important for proper function of the HPI implemented fifo.
*
www.eeworm.com/read/251598/12331272
cmd try2.cmd
/* Restrictions : The memory definitions MUST be preserved: VECTORS, XFER, SCRATCH, XFERHDR
and FIFO. FIFO is important for proper function of the HPI implemented fifo.
*
www.eeworm.com/read/251598/12331276
map test.map
/* Restrictions : The memory definitions MUST be preserved: VECTORS, XFER, SCRATCH, XFERHDR
and FIFO. FIFO is important for proper function of the HPI implemented fifo.
*
www.eeworm.com/read/250980/12372098
m dist_sqr.m
function d2 = dist_sqr(x1, x2)
%function d2 = dist_sqr(x1, x2)
%
% INPUTS:
% x1 - Matrix of N column vectors
% x2 - Matrix of M column vectors
%
% OUTPUT:
% d2 - M x N matrix of square d