target_image_gen

The short term energy function can be computed by splitting the speech signal into frames of N samples

说明：  matlab编写的时间序列分析工具，应用AR模型对时间序列进行预测(time series analysis written matlab tools, applications, time series AR model to predict)

除了蚁群算法，可用于PID参数优化的智能算法还有很多，比如遗传算法、模拟退火算法、粒子群算法、人工鱼群算法，等等。(In addition to the ant colony algorithm, can be used in the intelligent algorithm of PID parameter optimization and there are many, such as genetic algorithm, simulated annealing algorithm, particle swarm optimization (pso), artificial fish algorithm, and so on.)

Fuzzy neural network implementation

BuildFBITree function in the signal processing

这是一个关于多目标数据融合的很好的温章，希望对大家有所帮助。原理清晰，见解独特，希望对大家有所帮助(This is a multi-target data fusion on the temperature of a good chapter, we want to help. Principles of clarity, insight unique, want to help everyone)

源于谱分析的交通流预测，预测效果相当不错(From spectral analysis of traffic flow forecasting, prediction is quite good)

功能描述：测试LMS与RLS算法，比较两种算法的收敛特性 文件名：LMS_RLS_sim.m 测试用例： x(n)+a1*x(n-1)+a2*x(n-2)=e(n)，a1=-1.6,a2=0.81,e(n)为高斯白噪声 文件输出：系数a1的值 调用函数：function [A] = LMS_Algo(M,N,mu,xn) 被调用：无 作者：mingcheng 编写时间：2009-10-13 修改时间：2009-10-13 版本：V1.0 ( Function Description: Test LMS and RLS algorithm, the convergence characteristics were compared file name: LMS_RLS_sim.m test case: x (n)+ a1* x (n-1)+ a2* x (n-2) = e (n), a1 =- 1.6, a2 = 0.81, e (n) is Gaussian white noise file output: the value of coefficient a1 call the function: function [A] = LMS_Algo (M, N, mu, xn) is called: No of: mingcheng write time :2009-10-13 modified :2009-10-13 version: V1.0 )

一个MATLAB工具箱，可以进行快速而可靠的听觉阈值的计算！目前很少有类似的方法。(A MATLAB toolbox for rapid and reliable auditory threshold estimation)

基于蒙特卡洛方法的主动声纳信号检测性能分析.主动声纳信号检测性能的分析上,目前在计算机仿真中一般假定混响包络的统计特性符合瑞利分布模型。基于此模型,已经有了较完善的理论。然而,在现代高分辨声纳系统中,混响包络的统计特性并不符合瑞利分布模型。此时在接收机工作特性分析时存在大量繁琐的公式推导。因此该文采用蒙特卡洛(M onte Carlo)统计试验方法,实现对瑞利分布混响背景下的主动声纳信号检测性能分析。结合对接收机工作特性曲线的仿真,得出了检测概率的理论值和仿真结果的误差曲线。误差曲线表明,蒙特卡洛方法在主动声纳信号检测的性能评估中是可行的。 更多还原 (Active sonar signal detection performance analysis, computer simulation is generally assumed that the statistical properties of the reverberation envelope distribution model of Rayleigh active sonar signal detection performance analysis based on the Monte Carlo method. Based on this model, has been a better theory. However, in the modern high-resolution sonar system, the statistical characteristics of the reverberation envelope does not comply with the Rayleigh distribution model. At this point in the receiver operating characteristic analysis, there is a lot of tedious formula derivation. In this paper, using the Monte Carlo (M onte Carlo) statistical test methods, active sonar signal detection performance analysis reverberation background Rayleigh distribution. The receiver operating characteristic curve simulation obtained the error curve of the theoretical value and the simulation results of the detection probability. The error curve shows that the Monte Carlo method in the assessm)