least-squares

基于自适应滤波器的LMS算法仿真程序的计算部分(Based on the LMS adaptive filter algorithm for the calculation of part of simulation program)

基于年龄累计直方积累的人脸识别与鉴别算法比较(Cumulative Histogram Based on the accumulation of age, face recognition compared with the discrimination algorithm)

使用MATLAB进行GUI界面的编写 实现了 基本的串口通信，通过FT345bm硬件测试，可是实现115200bps的速率进行传输 ，性能比较稳定。(radar comm ,GUI ，usb ft245bm)

this program can simulate DBR OLED. structure of OLED is two DBR layer-anode-two grganic layer-cathode. with this program, ueser can optimize the thickness of DBR layer

经典jacobi算法求矩阵特征值，matlab程序设计(Classical Jacobi matrix algorithm for eigenvalues, matlab programming)

针对瞬时混合盲信号分离的自适应算法进行调研和比较，对于LMS，RLS算法（包括基于普通梯度和自然梯度两种）进行仿真验证，并对一些未知图像的混合进行分离。(Blind signal separation for instantaneous mixture algorithm for adaptive research and comparison, for the LMS, RLS algorithms (including gradient and natural gradient based on common two) for simulation, and some unknown mixture of image separation.)

对过河问题的建模仿真和求解，可用于数学建模课程和竞赛(Right across the river to solve the problem of modeling and simulation can be used for mathematical modeling courses and competitions)

基于最小二乘支持向量机理论,结合某风电场实测风速数据,建立了最小二乘支持向量机风速预测模型。对该风电场的风速进行了提前1h的预测,其预测的平均绝对百分比误差仅为8.55 ,预测效果比较理想。同时将文中的风速预测模型与神经网络理论、支持向量机(support vector machine,SVM)理论建立的风速预测模型进行了比较。仿真结果表明,文中所提模型在预测精度和运算速度上皆优于其他模型。 (Based on least squares support vector machine theory, combined with a wind farm measured wind speed data, the establishment of a wind vector machine forecasting model of least squares support. The velocity of the wind farm were predicted in advance 1h, the mean absolute percentage error of only 8.55 of its forecast, forecast effect is ideal. While the text of the wind speed forecasting models and neural networks, support vector machines (support vector machine, SVM) wind speed prediction models were compared with established theories. Simulation results show that our proposed model on prediction accuracy and computing speed are superior to other models.)

一种噪声辅助数据分析方法,基于人工神经网络的常用数字信号调制，信号维数的估计。( A noise auxiliary data analysis method, The commonly used digital signal modulation based on artificial neural network, Signal dimension estimates.)

achieving smallest MSE (in noise contamination)