smp75

人脸识别的源程序，用Matlab语言实现，可以参考看一下。(Face recognition source code, using Matlab language, can refer to a look.)

一个三维时域有限差分Finite Difference Time Domain, FDTD程序。希望对大家有所帮助。(A three-dimensional Finite Difference Time Domain, FDTD program. Hope helpful.)

autofocus digitla hologram reconstruction

经典的matlab程序100例，很适合初学Matlab的同胞们(Matlab classic 100 cases of the procedure, it is suitable for beginners compatriots Matlab)

接收天线对分布式干扰机群和单个大功率干扰机方向性影响数值计算及仿真(Receiving antenna directivity effects of numerical calculation and simulation of distributed interference fleet and a single high-power jammer)

Matlab使用pso进行svm参数优化寻优(Matlab were svm parameter optimization using pso optimization)

异步机直接启动最基本的仿真模型，希望对大家有用(Asynchronous machine directly start the basic simulation model, we hope to be useful)

This book includes nine examples that represent typical design tasks of an automotive engineer. It shows how The MathWorks modeling and simulation tools, Simulink® and Stateflow,TM facilitate the design of automotive control systems. Each example explains the principles of the physical situation, and presents the equations that represent the system. The examples show how to proceed from the physical equations to the Simulink block diagram. Once the Simulink model has been completed, we run the simulation, analyze the results, and draw conclusions from the study.

遗传算法优化神经网络的通用的matlab程序，希望对大家有帮助(Genetic algorithm optimization neural network)

一个身体部位比较模型的新方法网络（BAN）的，可以容纳多个环节和多个科目。所述的绝对测量允许跨频谱可能刻画的比较 从单参数为整个合奏，通过基于参数化到每个活动，每个学科和每个环节模型。使用错误，并明确之间权衡复杂性，在一个善良的适应措施相结合，显示有重要的影响时，适用于一系列典型的禁止通道数据。它是有不同的 在模式的选择的影响，以及它相关的复杂性，混合活动的“日常”的数据，设置活动相比，动态数据（例如步行）。平均路径损耗的不足，甚至位数的路径损失的措施，作为唯一的表征还强调“禁止通道。 (A new approach to compare models for body area networks (BAN) that accommodates multiple links and multiple subjects is presented. The absolute measure described allows comparison across a spectrum of possible characterizations ranging from single-parameter for an entire ensemble, through to per-activity, per-subject and per-link based parameterized models. The use of an explicit trade-off between error and complexity, combined in a goodness-of-fit measure, is shown to have important consequences when applied to a range of typical BAN channel data. It is shown that there are different implications in choice of model, and it’s associated complexity, for mixed-activity “everyday” data, when compared with set-activity dynamic data (e.g. walking). The deficiency of mean path loss, or even median path loss measures, as a sole characterization of the BAN channel is also highlighted.)