DSP0404

东北大学研究生上课时数字图像处理课的课件(Northeastern University graduate class of digital image processing course courseware)

Wykorzystufec kowariancyjnq equations form a sequential least-squares estimation metodq, determine the updated values sequentially wspotczynnikow discrete approximation of the object model (1) for successive k-those moments in time.

数字信号处理、图像处理 中值定理有关原理内容 快速算法(Digital signal processing, image processing, the mean value theorem principle content Fast Algorithm)

matlab code that generates input file for gridgen to make automated mesh in conical and bell shape nozzles

说明：  基于神经网络的传感器建模仿真和传感器动态补偿方法(Sensors based on neural network modeling and simulation, and dynamic compensation method)

说明：  matlab与 人工神经网络2007 配套源程序(matlab and artificial neural network supporting source, 2007)

used to filter the latent state variable

样本加权模糊聚类，可用于各种功能，只需改变输入即可(Sample weighted fuzzy clustering can be used for various functions, simply by changing the input to)

该函数用来计算时间序列的最大Lyapunov 指数 Wolf 方法 m: 嵌入维数 tau:时间延迟 data:时间序列 N:时间序列长度 P:时间序列的平均周期,选择演化相点距当前点的位置差，即若当前相点为I，则演化相点只能在|I－J|>P的相点中搜寻 lambda_1:返回最大lyapunov指数值 (This function is used to calculate the time series of the largest Lyapunov exponent Wolf method m: embedding dimension tau: time delay data: time series N: Time sequence length P: the average period of time series, the evolution of the current location of the point relative pitch poor, that is, if the current phase point is I, the evolution of the phase point only | I-J |> phase point P in search lambda_1: returns the maximum index value lyapunov)

本文先用灰色GM(1,1)模型对陕西省GDP 做预测, 经过检验, 再用此模型确定另外一些未知指标, 最后通过确定的这些指标用 灰色GM(1,N)模型作预测, 通过比较总结两种模型各自的特点, 从而科学的指导陕西省经济发展,国内生产总值预测模型具有重要的现实意 义。 (This article first gray GM (1,1) models do forecast GDP of Shaanxi province, on examination, then this model to determine other unknown targets, and finally through the identification of these indicators of gray GM (1, N) model for prediction, by Comparison of two models summarize the characteristics of their own, so the guidance of scientific economic development in Shaanxi Province, China' s GDP forecast model has important practical significance.)