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小波变换在图像压缩中的应用，都是完整的论文，希望能对大家有所帮助(Wavelet transform in image compression, are full of papers, hoping to be helpful)

能量检测,主要是看如果根据虚警概率得到门限，然后进行判决(enengy detection)

说明：  提供了各种调制手段之下的通信BER仿真结果，并且运用MALAB的simulink加以实现(programs for the communication BER modulation)

关于matlab信道仿真中经常用到的信道噪声函数，包括高斯白噪声，瑞利信道，赖斯信道的仿真(Channel simulation on matlab frequently used function of channel noise, including Gaussian white noise, Rayleigh Road, Lai Sixin Road Simulation)

计算高速摄影机拍摄的两幅图片中物体的移动速度(Calculation speed camera captured two images of objects in the speed)

此文件包含着EEMD的能量特征分量的计算程序和EEMD之后进行各个IMF的KL散度指的计算程序。(This file contains the energy characteristic component EEMD computational procedures and after each EEMD KL divergence refers to the IMF s calculation program.)

performance evaluation of hanndover trigger condiotion estimation

厦门大学屈小波老师2014年图像融合新文及matlab代码。(High quality multi-focus image fusion using self-similarity and depth information )

MATLAB语言常用算法程序集,包含了大量的实例程序(MATLAB language programs, including a large number of example programs)

高速铁路路基沉降是一个复杂的系统过程,涉及不同时期、不同工况,选用单一的预测模型不足以反映路基整体的变形规律.Logistic模型及Verhulst模型的曲线均为S形,可以反映全过程的地基沉降与时间的关系.针对路基填筑期和降水期两个时段利用MATLAB软件编制程序计算模型参数,得到Logistic模型和灰色Verhulst模型,进而求得两者的最优加权组合模型.对比结果表明:在路基填筑期由两者的最优加权组合模型预测得到的结果与实测结果较吻合,拟合精度高于单一模型 而在降水期Verhulst模型的预测值更接近实测值,平均相对误差约为1.75％,拟合精度较高.(High-speed railway subgrade settlement process is a complex system involving different times and in different conditions, the choice of a single forecasting model does not adequately reflect the overall deformation of roadbed. Curve Logistic model and Verhulst models are S-shaped, the whole process can be reflected foundation settlement versus time. against roadbed construction period of two hours and precipitation using MATLAB software programming model parameters, the Logistic model and gray Verhulst model, and then get the optimal model of a weighted combination of the two. comparative results indicate : results and experimental results in the roadbed construction period by the weighted combination of the best of both models predicted than the anastomosis fitting accuracy than a single model precipitation predicted value of Verhulst model closer to the actual value of the average relative error approximately 1.75 fitting accuracy.)