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r43
- 鲁棒控制器设计，由于RBF网络可以实现任意逼近的非线性关系，它的目标是要做到误差平方和最小，与非线性PCA的目标一致，所以上述非线性PCA的模型可以通过采用两个RBF网络来实现非线性正变换 和反变换 。RBF网络是一个三层前馈网络，隐层采用径向基函数作为激励函数。第一个RBF网络把高维空间的数据映射到低维空间（如图4），第二个RBF网络将前面网络输出的低维空间数据再映射到高维空间，实现数据恢复(如图5)。这两个网络分别进行训练。-robust controller design, as RBF
FourierSeriesApproach
- 此算法为求一般的傅里叶级数逼近逼近的一般算法-algorithm for the sake of the general Fourier series approximation of the general approximation algorithm
amerdow
- 哈密尔顿近似算法的语言实现及旅行商问题的实现-Hamilton approximation algorithm language and the achievement of Traveling Salesman Problem
TLC2543profile
- TLC2543的中文简介,附有汇编操作,TLC2543是德州仪器公司生产的12位开关电容型逐次逼近模数转换器，它具有三个控制输入端，采用简单的3线SPI串行接口可方便地与微机进行连接，是12位数据采集系统的最佳选择器件之一。本文介绍了该芯片的功能、时序，并给出了8051单片机的接口电路。-TLC2543 briefed the Chinese, with the compilation operation, TLC2543 is by TI Switched-Capacitor 12-succe
44b0_Adc
- S3C44B0X 具有 8 路模拟信号输入的 10 位模/数转换器（ADC），它是一个逐次逼近型 的 ADC，内部结构中包括模拟输入多路复用器，自动调零比较器，时钟产生器，10 位逐次 逼近寄存器（SAR），输出寄存器如下图所示。这个 ADC 还提供可编程选择的睡眠模式， 以节省功耗。 -S3C44B0X with eight analog signal input to the 10 analog / digital converter (ADC), It is a succe
exa070501
- 共轭正交镜像滤波器组的设计。令N=22,wp=0.45pi,用切比雪夫最佳一致逼近法设计单带滤波器G(z),在得到半带滤波器Hlf(z). -conjugate mirror filters orthogonal design. Order N = 22, wp = 0.45pi. Chebyshev with the best approximation consistent single-band filter design G (z), with the half-band filte
MLS1DShape
- 求解无网格法的近似函数，（伽辽金无网格法移动最小二乘近似程序）-for non-grid method similar function (Galerkin grid Mobile least squares approximation procedures)
拟合与逼近
- 拟合与逼近的C程序-fitting approximation with the C program
ckeil
- 目前已有若干版本的子程序库公开发表，它们各有特色。本程序库中的开平方算法为快速逼近算法，它能达到牛顿迭代法同样的精度，而速度加快二十倍左右，超过双字节定点除法的速度。 -there are several versions of the subroutine library published their own characteristics. The library opened in the square approximation algorithm for rapid algorith
richardson.cpp
- richardson algorithm of approximation of integrals
approximationmethod
- 该程序基于VB语言实现函数逼近法求极点，结果保存在access数据库中-The program based on VB language function approximation method , the results are saved in access databases
prtree-1.7.tar
- Since objects stored in a spatial can be rather complex they are often approximated by simpler objects, and spatial indexes are then built on these approximations. The most commonly used approximation is the minimal bounding box: the smallest
sons
- Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear mod