forward33

基本调制识别。识别2ask，2fsk，2psk，4ask，4fsk，4psk。(The basic modulation recognition. Identification 2ask, 2fsk, 2psk, 4ask, 4fsk, 4psk.)

本包内为 WORD 文档，内涵四个程序代码，分别是利用BP网络和指数平滑法，对数据进行预测用的(WORD documents within the package, meaning the four program code, respectively, the use of BP networks and exponential smoothing, forecasting the data)

matlab实现的感知机应用上的实例，对其具体功能的加深认识(matlab implementation of Perceptron application examples to deepen understanding of their specific functions)

计算混沌序列的分形维数，内附有洛伦兹序列和哈农序列，可以根据自己所需，产生感兴趣的序列，自行添加。(Fractal dimension calculation chaotic sequence, the sequence is enclosed and Hanon Lorentz sequence, can according to their required to produce a sequence of interest, add their own.)

说明：  计算函数的极值的一种方法 只是其中一种 以后会陆续上新的(Calculation of the extremal function is just one of a method of the future will continue on a new)

用MATLAB实现遗传算法解决0-1背包问题。 赌轮选择，单点交叉，变异(GA_MATLAB about 0-1knapsack problem roulette wheel selection; single-point crossover; variation;)

matlab实现的一个无迹卡尔曼滤波（UKF）程序（纯方位系统），可以用于目标跟踪领域。(matlab implementation of an unscented Kalman filter (UKF) program (Bearings), can be used for target tracking.)

newmark and wilson theta mehtod

DTW（Dynamic Time Warping，动态时间归整）算法，该算法基于动态规划（DP）的思想，解决了发音长短不一的模板匹配问题，是语音识别中出现较早、较为经典的一种算法。用于孤立词识别，DTW算法与HMM算法在训练阶段需要提供大量的语音数据，通过反复计算才能得到模型参数，而DTW算法的训练中几乎不需要额外的计算。所以在孤立词语音识别中，DTW算法仍然得到广泛的应用。 (DTW (Dynamic Time Warping, dynamic time warping) algorithm based on dynamic programming (DP) ideas, sounds of varying lengths to solve the template matching problem, is speech recognition appeared earlier, more classic kind of algorithm. For isolated word recognition, DTW algorithm and HMM algorithm in the training phase need to provide a large number of voice data, obtained by repeated calculations to model parameters, while the DTW algorithm is almost no additional training calculations. Therefore, in isolated word speech recognition, DTW algorithm is still widely used.)

A speech signal filterbank, using melscale frequency and framebanking.( 1. For speech signal can be represented as a discrete sequence of frames (or feature vectors) that can be used as the input to a speech recogniser. Important ideas and techniques that are used in the assignment are the design of a (Mel frequency scale) audio filterbank, , windowing of a continuous audio signal, spectrum analysis of the signal, filtering as multiplication in the frequency domain, the visual representation of a speech signal as a spectrogram, appreciation of the acoustic variability in real speech utterances. 2. To gain a deeper knowledge of the application of MATLAB programming to audio signal processing. 3. To gain practice in the art of writing a formal report: structure, content, style, use of diagrams, presentation etc. etc. )