modul3_FDTD

the best model of a scorbot with 6 dof

基于matlab仿真的一段程序 是刚开始学习控制类课程的好材料 可以好好地参考一下哦(Matlab simulation of a program is just beginning to learn to control courses materials can have a good reference )

this code is about QRS detection in ECG signal. you have to enter the signal data, and the output is the position of the Q and R and S wave.

RLS算法主要适用于数字信号处理的fir和iir数字滤波器(RLS algorithm )

TSP solved by genetic algorithms

：介绍了扩展卡尔曼滤波算法和无迹变换(unscented transformation，UT)算法，并对扩展卡尔曼滤波算法(EKF)和无 迹卡尔曼滤波算法(UKF)进行比较，阐明了UKF优于EKF。在此基础上，提出了一种基于Unscented变换(uT)的高斯和滤 波算法，该算法首先通过合并准则得到适当个数的混合高斯模型，逼近系统中非高斯噪声的概率密度(: Introduction of the extended Kalman filter algorithm and unscented transform (unscented transformation, UT) algorithm, the extended Kalman filter algorithm (EKF) and unscented Kalman filter (UKF) for comparison to clarify the UKF is superior to EKF. On this basis, we propose an approach based on Unscented Transform (uT) and the Gaussian filtering algorithm, which first of all, by merging the appropriate number of criteria to be a mixture of Gaussian model, which was close to the system of the Central African Gaussian noise probability density)

直接序列扩频和跳频扩频直接序列扩频和跳频扩频(直接序列扩频和跳频扩频)

Object MatLab implementation of the Robust Non-Linear Smoother (RNLS) for state-space models

Low-density parity-check (LDPC) codes have recently emerged due to their excellent performance. However, the parity check (H) matrices of the previous works are not adequate for hardware implementation of encoders or decoders. This paper proposes a hybrid parity check matrix which is efficient in hardware implementation of both decoders and encoders. The hybrid H-matrices are constructed so that both the semi-random technique and the partly parallel structure can be applied to design encoders and decoders.

Linear discriminant analysis (LDA) and the related Fisher s linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.