PRP_2

border segmentation for CBIR system using matlab

说明：  完整的QPSK的调制与解调，已调试通过，认真学习一下(QPSK modulation and demodulation)

通过对RSSI测距模型进行分析， 并提出一种针对室内环境的参数修正方案。 通过 自行研发的传感器节点，上进行验证分析，实验表明，采用环境参数修正方案后， 明显提高了测距的精度。(We studied andanalyzed RSSI—based distance estimated model, and provide aparameter calibration method which in specific to indoor environmental applications．Experience on our prototype node)

Evop algorith for optimization

this is clipping code for papr reduction in matlab.In this code clipping is fillowed by filtering to reduce inband interference.Simulated results are in the form of graphs to compare performance

This is a simulation of BPSK modulation and its perfomane

在机动目标跟踪中，机动目标模型是机动目标跟踪的基本要素之一，一般希望机动目标模型能准确表征目标机动时的各种运动状态。比较常用的模型有匀速运动(CV)模型、匀加速运动(CA) 模型、时间相关模型（Singer）和机动目标“当前”统计模型。上述模型均采用机动频率表征目标的机动情况。在应用当中，通常采用固定的机动频率，这就表示机动目标的机动时间是一定的，而实际上机动目标的机动时间是不断变化的，也就是说机动频率是不断变化的，采用固定机动频率必然会带来误差。采样周期在0.5—2S时，机动频率越小跟踪精度越高[1]，但机动频率仍然是固定值。本文提出的基于神经网络的机动频率自适应调整方法可以使机动频率随机动而变化，从而提高状态估计的准确性，提高跟踪精度。本文将小波神经网络用于机动目标跟踪中机动频率的自适应调整，该算法对机动目标“当前”统计模型中的机动频率进行实时修改, 从而自适应的改变机动频率,使跟踪算法与目标的真实状态更接近。该算法采用小波神经网络的离线训练，实时性好。(The maneuver of the maneuvering target is uncertain. The maneuvering frequency is constantly changeable, but traditionally it is beforehand determined as a constant based on the target state estimation in the state model of the maneuvering target. The maneuver of the maneuvering target makes the kinematics equation of the target model mismatch with the practical motion model and the tracking error will be increased. Based on the advantages of the self-learning, the rapid convergence rate and the nonlinear approximation ability of the wavelet neural network, it was put forward to be used in the field of target tracking in the paper. The new residual is used as the input of the wavelet neural network, the output of the network is used to adjust adaptively the maneuvering frequency of the CS model. The algorithm is more close to the real state of the target. The simulation results showed that tracking error can be reduced and the tracking accuracy can be improved.)

通过比较奇异谱图和高阶奇异谱图得出结论：高阶奇异谱分析能够更好的二次确定嵌入维数。最后根据Takens嵌入定理进行相空间的重构。(By comparing the spectra of singular spectrum and higher-order singular conclusion: High singular spectrum analysis to better determine the embedding dimension of the secondary. Finally, according to Takens embedding theorem for phase space reconstruction.)

将元素写成VTK文件，一般是元胞数组，可以实现VTK数据的读写(Elements written in VTK file general cellular array can achieve VTK data read and write)

各种matlab程序。。。。。。。。。。。。。。。。。。。。。。。。。。。。(four bars)