bxputwck

精通MATLAB7.0,是一本很好的学习MATLAB的书籍.(Proficient MATLAB7.0, are a very good study MATLAB books.)

Fixed-point for functions of several variables (Function fixed_point_systems(x0, N) approximates the solution of a system of nonlinear equations F(x) = (f1(x), f2(x), ..., fn(x)) = 0 rewritten in the fixed-point form x = G(x) = (g1(x), g2(x), ..., gn(x)). This is done by the user at the bottom of the file. The sub-function G(x) has to be updated accordingly with the given system. The iteration scheme x(k+1) = G(x(k)) is implemented until condition |x(k)- x(k-1)| < tol is met, starting with an initial approxiamtion vector x0. If, after N iterations, the stopping criterion is not reached, a message concerning the iterated x s is displayed. the output consists of iterates of each variables x1, x2, ..., xn in each column. )

FCCUWB，关于UWB的FCC规范的频谱图，给出了相应的说明和解释(FCCUWB, on the FCC UWB standard spectrum, the corresponding description and explanation)

基于matlab的数值积分算法，用代码编写实现，含键控输入模块。(failed to translate)

matrice fondamentale

适合初学者的很好的永磁同步电机仿真模型，模型十分清晰(Good for beginners simulation model of permanent magnet synchronous motor, the model is very clear)

转速环的MATLAB仿真，感觉效果 挺不错的。(MATLAB simulation speed ring, I feel very good results.)

采用MATLAB编程，采用遗传算法求分段函数极值(Using MATLAB programming, using genetic algorithm for segmentation function extremum)

实现无线传感器网络分簇路由算法的程序，可以运行的。( clustering routing for Wireless sensor network , the programs can run.)

BP神经网络：是一种按误差逆传播算法训练的多层前馈网络，是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层（input）、隐层(hide layer)和输出层(output layer)。(BP neural network: a Press the front back propagation algorithm to train multilayer feedforward network is one of the most widely used neural network model. BP network can learn and store large amounts of input- output mode mappings without prior reveal mathematical equations that describe this map. It' s learning rule is to use the steepest descent method, through a reverse spread to constantly adjust the network weights and thresholds, so that the minimum squared error of the network. BP neural network topology, including the input layer (input), hidden layer (hide layer) and output layer (output layer).)