expfft

数据挖掘中K均值算法的实现用MATLAB编写(data mining to the K-means algorithm to achieve prepared using MATLAB)

iradon1 function with matlab

A working setup that focuses on dimensional prediction of emotions from spontaneous conversational head gestures. It maps the amount and direction of head motion, and occurrences of head nods and shakes into arousal, expectation, intensity, power and valence level of the observed subject as there has been virtually no research bearing on this topic. Preliminary experiments show that it is possible to automatically predict emotions in terms of these five dimensions (arousal, expectation, intensity, power and valence) from conversational head gestures. Dimensional and continuous emotion prediction from spontaneous head gestures has been integrated in the SEMAINE project [

用MATLAB编制的威赫斯特模型 可以用于灰色预测(Compiled with MATLAB can be used for gray prediction model Weihesite)

matlab code for bayseian algorithm

说明：  gps系统的仿真举例，主要是功率谱密度的仿真。结果正确。(gps system simulation for example, is the power spectral density of the main simulation. Was correct.)

详细介绍了matlab中用于图像处理的函数及其用法，对初学者很有用(Details of the matlab image processing functions for its usage, it is good for beginners)

Fminsearch does not admit bound constraints. However simple transformation methods exist to convert a bound constrained problem into an unconstrained problem.

有m台不同的机器，n个不同的工件。每个工件有多道工序，每道工序由指定的机器在固定的时间内完成。一道工序一旦开始处理，就不能中断。每台机器一次只能处理一道工序。一个调度就是决定每台机器上工序的处理顺序，使得机器完成所有工件的时间最短。具体的，该问题就是要求在满足（1）、（2）两个约束条件的前提下，确定每台机器上工序的顺序，使加工的时间跨度（从开始加工到全部工件都加工完所需要的时间）达到最小。其中，（1）表示工件约束条件：对每个工件而言，机器对它的加工路线是事先确定的；（2）表示机器约束条件：对每台机器而言，一次只能对一道工序进行加工。()

％ PURPOSE : Demonstrate the differences between the following filters on the same problem: ％ ％ 1) Extended Kalman Filter (EKF) ％ 2) Unscented Kalman Filter (UKF) ％ 3) Particle Filter (PF) ％ 4) PF with EKF proposal (PFEKF) ％ 5) PF with UKF proposal (PFUKF)( PURPOSE: Demonstrate the differences between the following filters on the same problem: 1) Extended Kalman Filter (EKF) 2) Unscented Kalman Filter (UKF) 3) Particle Filter (PF) 4) PF with EKF proposal ( PFEKF) 5) PF with UKF proposal (PFUKF))