Cyclostationary

蚁群算法的matlab源码,对matlab初学者有一定帮助，对了解蚁群算法也有易处(Ant colony algorithm matlab source)

谱减法语音增强，包含基本谱减法，多带谱减法，以及自适应谱减法。(Spectral subtraction speech enhancement, contains the basic spectral subtraction, multi-band spectral subtraction, and adaptive spectral subtraction)

lmd 采用滑动平均处理，调整过，可以直接运行出图。(lmd hua dong pingjun)

ON THE CAPACITY OF THE MIMO CHANNEL - A TUTORIAL INTRODUCTION

the code i have uploaded estimate the position of speaker,in environment put a number of microphones that by extended kalman filter estimate the position of speaker

Analyze a performance of cooperative networks over Rayleigh fading channels for different transmissions protocols.

卡尔曼滤波器的主要功能就是目标跟踪，程序利用卡尔曼滤波器实现了对机动目标的跟踪(Kalman filter is the main function of target tracking, procedures for the use of a Kalman filter to achieve the right track moving targets)

在运载体运动情况下,提出了一种适用于捷联惯导系统(SINS)初始对准的新算法,该算法以惯性空 间为过渡参考基准,即建立了初始时刻惯性坐标系(i0系)和初始时刻捷联惯组惯性坐标系(ib0系)两个惯性坐标 系。将捷联惯组坐标系(b系)与导航坐标系(n系)之间的初始对准姿态矩阵的实现分解为三步骤:(1)通过地理 位置和初始对准时间求解i0系至n系的变换矩阵 (2)通过惯导比力方程变形,引入测速仪速度辅助,求解从ib0 系至i0系的常值变换矩阵 (3)使用姿态更新算法实时计算b相对于ib0系的变换矩阵。最后,载车运动环境下的 初始对准试验结果表明航向角对准精度达到了0.1b(1R)。 (On the moving base, a new initial alignment algorithm for strapdown inertial navigation system (SINS) is proposed. In this algorithm, two special inertial frames, the initia-l time inertial frame (i0frame) and the initia-l time SINS body inertial frame (ib0frame), are defined and are selected as transition reference frames. The calculation of initial alignment direction cosine matrix (DCM) between SINS body frame (bframe) and nav- igation reference frame (nframe) is expanded into three parts: (1) the DCM betweeni0frame andnframe is easily obtained via local geographical coordinates and initial alignment time (2) by expressing SINS specific force equation inbframe and by the aid of external velocity log, the constant DCM fromib0frame toi0frame is achieved (3) attitude updating using gyro samples gets the DCM betweenbframe andib0frame. In the end, some vehicular tests are carried out on the moving base and the accuracy of azimuth reaches about 0.1b(1R). )

倒立摆的模型和PID控制，Simmechanic 模型和控制(Inverted pendulum model and PID control, Simmechanic model and control)

this is my first code in matalab that i have uploaded