c_and_f

递归神经网络-实时学习训练算法代码，亲测可用，简洁无误，容易上手。( Recursive neural network- real-time learning training algorithm code, pro-test available, simple and correct, easy to use.)

PRE IN POST OREDER TRAVERSAL C++ CODE VISUAL

计算重力异常,只需要输入最大重力场模型的最大阶数以及重力场模型文件名在程序里设置经纬度范围和间隔即可得到重力异常(Gravity anomaly)

arithemetic code on visual c++

PMV，的热舒适指标计算程序VB编码，可供参考(PMV, thermal comfort index calculation program VB code, for reference)

说明：  几种模幂算法，有传统模幂，SMM模幂，基于2的K次方的模幂和最一般的模幂算法，还有为这些模幂算法建立的WINDOWS对话框。可以方便的运行。(algorithm, the traditional mode power, SMM Modular Power, Based on two of the K-th power module and the most common mode power algorithm, These modules also for the establishment of the algorithm Power Windows dialog box. To facilitate the operation.)

适用于大型稀疏矩阵 矩阵转置 c语言 来自于有限元方法编程(From the finite element method suitable for large-scale sparse matrix matrix transpose c language programming)

Orthogonal Polynomials Approximation 数值分析，计算正交基多项式的系数 (Given a function f and a set of m >0 distinct points . You are supposed to write a function to approximate f by an orthogonal polynomial using the exact function values at the given m points with a weight assigned to each point . The total error must be no larger than a given tolerance. Format of function int OPA( double (*f)(double t), int m, double x[], double w[], double c[], double*eps ) where the function pointer double (*f)(double t) defines the function f int m is the number of points double x[] contains points double w[] contains the values of a weight function at the given points x[] double c[] contains the coefficients of the approximation polynomial double*eps is passed into the function as the tolerance for the error, and is supposed to be returned as the value of error. The function OPA is supposed to return the degree of the approximation polynomial. Note: a constant Max_n is defined so that if the total error is still not small enough when n = Ma)

基于FLUENT软件的一些常用UDF实例，比较有帮助(udf example)

在visual studio的平台上开发CUDA程序实现并行加速计算矩阵的乘积，同时比较与串行计算的差异(Differences in the development of procedures to achieve parallel CUDA accelerated computing matrices in visual studio platform, but compared with the serial computing)