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Simulation of Spatial Multiplexing system using 16-QAM with MLSE equalizer.

HSSVM是一个用超球SVM（Hyper-Sphere Support Vector Machines）模型求解多分类问题的工具包，采用Java语言实现。开发该程序的主要目的，是利用超球SVM求解模型代替传统上借助于解二分类问题的经典SVM模型来求解多分类问题。本文将论述该程序的主要实现细节，包括相关算法及设计原理的描述。(HSSVM is an ultra ball SVM (Hyper-Sphere Support Vector Machines) to solve multi-classification model of tool kit, using Java language. Development of the program' s main purpose is to solve the model by Ball SVM instead of the traditional means of solving two classification problems on the classical SVM model to solve multi-classification problems. This article discusses the main implementation details of the program, including related algorithms and design principles are described.)

To apply spatial filtering for an image

Normal ECG test taken on 250 Hz (sampling frequency) You can use in order to obtain (and compare) the stress (from HRV) (compare with ecg stroop & ecg matematica )

Solving Engineering Problems Using MATLAB C++ Math Library Introduction In the previous article, we studied how can use MATLAB C API to solve engineering problems. In this article I will show you how can use MATLAB C++ math library. The MATLAB® C++ Math Library serves two separate constituencies: MATLAB programmers seeking more speed or complete independence from interpreted MATLAB, and C++ programmers who need a fast, easy-to-use matrix math library. To each, it offers distinct advantages.

飞机设计的控制算法，为设计提供依据。程序为本人编写，不要外传(Aircraft design control algorithms, provide the basis for the design. I write procedures, not rumors)

matlab教程，适用于初学者，简明易懂。教程主要为matlab基础操作。(Matlab tutorial, it is suitable for beginners, concise, easy to understand. The main matlab tutorial for basic operations. )

Quinlan的决策树程序C4.5（M语言编写）(the program for decision tree C4.5 purposed by Quinlan )

实现bpsk，qpsk等调制方式的识别用于调制识别的代码，通过提取特征参数，(For modulation recognition code, through the extraction of characteristic parameters, implementation bpsk, qpsk forms of identification, such as modulation)

说明：  提出一种受灰狼（Canis lupus）启发的新的元启发式方法，称为灰狼优化器（GWO）。 GWO算法模仿自然界中灰狼的领导等级和狩猎机制。(This work proposes a new meta-heuristic called Grey Wolf Optimizer (GWO) inspired by grey wolves (Canis lupus). The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature.)