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蚁群算法求解旅行商问题matlab源程序,可画图.(Ant colony algorithm for traveling salesman problem (matlab source code), the algorithm has a drawing function.)

Hilbert-Huang变换之EMD分解程序。可以直接运行，以及附有几个详细例子。可以用以对非线性非平稳信号的处理，效果理想。(Hilbert-Huang transform EMD decomposition process. Can be run directly, as well as with several detailed examples. Can be used for non-linear non-stationary signal processing, the results are satisfactory.)

单径赖斯衰落信道模型源代码,该代码形成于瑞利衰落信道的基础之上(rician fading channel estmation)

本文介绍了一种基于核函数的参数估计方法，对于初学者来讲很有帮助(kernel based estimation )

说明：  该程序为关于pcm编码和pcm解码的matlab实现(The program on the pcm coding and decoding matlab achieve pcm)

说明：  The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):

该源代码应用于对传感器接收到的原始时域信号进行c扫描成像，应用于无损检测领域。(The source code is applied to the sensor receives the original time-domain signal c-scan imaging, used in non-destructive testing in the field.)

《matlab40个经典案例》书本PDF扫描版和源程序。福利继续上。欢迎指教(" Matlab40 a classic case of" book PDF scan version and source code. Benefits continue on. Welcome advice)

数学建模案例MATLAB实用程序百例 涵盖基本的matlab程序，对初学者很有帮助(Mathematical modeling case cases of MATLAB utility covers basic matlab program, very helpful for beginners)

ITML Information theroy metric learning 基于信息理论的度量学习(Information theroy metric learning)