サンプル(C++) 労力をあまり掛けずに済ませたので適当。 #include <cv.h> #include <highgui.h> #include <stdio.h> IplImage* src = 0; IplImage* src_f = 0; IplImage* image = 0; IplImage* dest = 0; IplImage* dest_mag = 0; IplImage* kernelimg=0; IplImage* big_kernelimg=0; CvMat * kernel=0; int kernel_size =21; int pos_var = 50; int pos_w = 5; int pos_phase = 0; int pos_psi = 90; void Process(int pos) { //CvFileStorage *fs = cvOp
Overview Extreme Learning Machines (ELM): Filling the Gap between Frank Rosenblatt's Dream and John von Neumann's Puzzle - Network architectures: a homogenous hierarchical learning machine for partially or fully connected multi layers / single layer of (artifical or biological) networks with almost any type of practical (artifical) hidden nodes (or bilogical neurons). - Learning theories: Learning
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ここのソースをちょこっと改造しただけ。 ---- コード(Python側) testmodule.py ---- # -*- coding: utf-8 -*- def testplus(i, j): return i + j + 3 ---- コード(C++側) ---- #include <Python.h> #include <iostream> #include <string> #include <sstream> #define VARNAME(var) #var // ---- exception ---- class PythonException { protected: const char* message_; const char* varName_; public: static const char* errorMessge_ImportModule; stat
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