snakeladder

iir滤波器对有噪语音滤波,在matalb上实现(IIR filter noisy speech filtering, on matalb)

这是一个基于线性矩阵的神经网络控制程序，它比普通的更简单，因为其应用的参数较少。(This is a learning model for matrix-based data. It can be more efficient than standard vector-based models when the training sample is small or the inputs are matrices, since this model has less parameters than standard ones and exploits an inner structure of the inputs)

Human Computer Interaction

籽子群优化算法优化BP神经网络，使用优化后的神经网络对图像进行分割。包括：籽子群优化算法，籽子的编码，最优权值和阈值的后成，基于籽子群优化算法的神经网络的培训，图像的分割。(The BP neural network optimized by Particle Swarm Optimization　algorithm for image segmentation)

IEEE文献Bayesian Compressive Sensing及贝叶斯压缩感知源码(Bayesian Compressive Sensing Code)

SC-FDMA性能分析，及与FDMA误码率比较(SC-FDMA performance analysis, and compared with FDMA for BER)

说明：  用有效独立法实现传感器优化布置，效果一般，但可供借鉴(Using the effective independence method to realize the optimal arrangement of sensors)

这个压缩包里包含有有关c和matlab混合编程的一些例子，是我从有关书的光盘中拷贝过来的。欢迎大家下载。(the compressed bundle contains the c and Matlab programming mixed some examples I take it from the book CD-ROM copy overnight. Welcome to download.)

Direct torque control for IM drives

把辨识分成两步进行：第一步：利用相关分析法获得对象的非参数模型（脉冲响应或相关函数）；第二步：利用最小二乘法、辅助变量法或增广最小二乘法等，进一步求的对象的参数模型。如果模型噪声与输入无关，则Cor-ls相关最小二乘法（二步法）可以得到较好的辨识结果。Cor-ls相关最小二乘法（二步法）实质上是先对数据进行一次相关分析，滤除了有色噪声的影响，再利用最小二乘法必然就会改善辨识结果。能适应较宽广的噪声范围，计算量不大，初始值对辨识结果影响较小。但要求输入信号与噪声不相关(The identification is divided into two steps: the first step: using the correlation analysis method for object nonparametric model (impulse response or related function) The second step: using the least squares method, auxiliary variable method or augmented least squares method and so on, further for the parameters of the object model. If the model input noise and independent, the Cor- ls related least squares (two footwork) can get good recognition results. Cor- ls related least squares (two footwork) is essentially the data to a correlation analysis, filter in addition to the influence of colored noise, using least squares inevitable will improve the identification result. To adapt to a wide range of noise and calculation is not big, the initial value to identification results less effect. But for the input signal and noise are not related)