mygui

正交信号校正法主要用于近红外光谱矩阵的预处理。其原理是将光谱阵与全氮含量阵正交,滤除光谱与因变量Y阵无关的信号,再建立定量校正模型,达到简化模型及提高模型预测能力的目的。(Orthogonal Signal Correction(OSC) removes variance in the X-block which is orthogonal to the Y-block. Such variance is identified as some number of factors (described as components) of the X-block which have been made orthogonal to the Y-block. When applying this preprocessing to new data, the same directions are removed from the new data prior to applying the model.)

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TRAINPSO is a network training function that updates weight and bias values according to particle swarm optimization.

a design methodology is introduced that blends the classical PID and the fuzzy controllers in an intelligent way and thus a new intelligent hybrid controller has been achieved. Basically, in this design methodology, the classical PID and fuzzy controller have been combined by a blending mechanism that depends on a certain function of actuating error. Moreover, an intelligent switching scheme is induced on the blending mechanism that makes a decision upon the priority of the two controller parts namely, the classical PID and the fuzzy constituents. The simulations done on various processes using the new hybrid fuzzy PID controller provides ‘better’ system responses in terms of transient and steady-state performances when compared to the pure classical PID or the pure fuzzy controller applications. The controller parameters are all tuned by the aid of genetic search algorithm.

神经元PID测试程序模型，方便好用，下载后可直接运行(Neuron PID model test program to facilitate the easy to use, the download can be run directly)

基于FCM的改进遗传算法步骤以及程序，内容清晰，过程详细而明确，结果清楚，很不错。(FCM based on improved genetic algorithm steps, and procedures, clarity, detail and clear process, the results clearly, very good.)

Given an output function f(x) and a cost function J(x) (and gradients), optimal inverse functions are found which produce the input x* with the lowest cost based on the current desired output. Output and cost functions produce a scalar. The method is demonstrated on 2D problems (for convenient visualization). With 2D plots removed (all but Figure 41), the code can run higher dimension systems also.

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hi my name is bhavesh pithva from gujarat i am a gtu student i upload a best papers for asics

基础的BP神经网络应用。附有注释，适合初学，简单易懂。(basic utilities of BP neural networks.)