The-realization--cellular-automata

These symbols are defined by vsyscall.o to mark the bounds of the ELF DSO images included therein.

The BCJR algorithm is an algorithm for maximum a posteriori decoding of error correcting codes defined on trellises (principally convolutional codes). The algorithm is named after its inventors: Bahl, Cocke, Jelinek and Raviv.[1] This algorithm is critical to modern iteratively-decoded error-correcting codes including turbo codes and low-density parity-check codes.

本程序模拟一个机器人躲避障碍的仿真.其中有不完善的地方 迫于精力有限,具体过程还有点粗糙,读者可以加以修正 (a simulation of the robot avoid obstacles to the simulation. Which forced the inadequacies in the energy are limited, There is a process in concrete rough, and readers can be amended)

introduction to various data class and its application in various domain

伪随机二位信号，用于系统辨识的特殊输入信号，可实现特定的功能，望多多学习。(Two pseudo-random signals for system identification of special input signal, to achieve specific functionality, hope to learn a lot.)

说明：  电动汽车永磁同步电机的卡尔曼滤波，强跟踪算法(Kalman filter and strong tracking algorithm for permanent magnet synchronous motor of electric vehicle)

基于遗传算法的自动组卷算法，能实现按照知识点、难度、区分度的自动试题提取组卷。(Automatic test paper based on genetic algorithm, can achieve according to knowledge, the difficulty of distinguishing the degree of automatic extraction of test paper questions.)

Fuzzy Auto PID Tuning for DC Motor The Fuzzy system needs 2 inputs e(t) & de(t) and it will get three outputs for tuning the PID gains (KP), (KI) & (KD) depending on the membership functions

支持向量机的程序，可以直接使用，对于初学者也很使用(Support vector machine (SVM) program, which can be used directly )

Training Artificial Neural Network. XOR Problem. Summation Units, Log-Sigmoid Neurons with Biases. Input Layer: 2, Hidden Layer: 2, Output Layer: 1 neurons. Returns mean square error between desired and actual outputs. Reference Papers: D. Karaboga, B. Basturk Akay, C. Ozturk, Artificial Bee Colony (ABC) Optimization Algorithm for Training Feed-Forward Neural Networks, LNCS: Modeling Decisions for Artificial Intelligence, 4617/2007, 318-329, 2007. D. Karaboga, C. Ozturk, Neural Networks Training by Artificial Bee Colony Algorithm on Pattern Classification, Neural Network World, 19(3), 279-292, 2009. */