Description: 功率谱估计的应用范围很广，在各学科和应用领域中受到了极大的重视。在《现代信号处理》课程中讲述了经典谱估计和现代谱估计这两大类谱估计方法；经典谱估计是基于傅立叶变换的，虽然具有运算效率高的优点，但是频谱分辨率低同时旁瓣泄漏严重，对长序列有着良好的估计。为了克服经典谱估计的缺点，人们开展了对现代谱估计方法的研究。现代谱估计是以随机过程的参数模型为基础的，有最大似然估计法、最大熵法、AR模型法、预测滤波器法。现代谱估计对短序列的估计精度高，同经典谱估计互为补充。在认真学习了现 代谱估计方法后，我选择了现代谱估计中的AR模型法的仿真作为题目。下面给出AR模型的相关理论和仿真实现。-Power Spectral Estimation of very extensive, in all disciplines and fields of application of a great deal of attention. The "modern signal processing" on the curriculum of classical and modern spectral estimation spectrum is estimated that the two types of spectrum estimation method; Classical spectrum estimation is based on Fourier transform, although high computing efficiency advantages, but also low-resolution spectrum Sidelobe serious leakage of long sequences have good estimates. In order to overcome the classic shortcomings of the spectrum estimation, there have been a pair of modern spectral estimation methods. Modern spectral estimation is the random process model parameters based on the maximum likelihood estimation, maximum entropy method, AR model, forecast filter. Spe Platform: |
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Author: |
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Description: describes the most common terms used in radarsystems, such as range, range resolution, Doppler frequency, and coherency.
The second part of this chapter develops the radar range equation in many of its forms. This presentation includes the low PRF, high PRF,search, bistatic radar, and radar equation with jamming.-describes the most common terms used in rad arsystems, such as range, range resolution, Doppler frequency, and coherency. The second part of this chapter d evelops the radar range equation in many of its f orms. This presentation includes the low PRF. high PRF, search, bistatic radar, and radar equation with jamming. Platform: |
Size: 8192 |
Author:alan |
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Description: 超分辨率复原（分成1024块）
将样本库中的高分辨率图象和低分辨率图象分别做分块处理，当新输入一幅低分辨率图象时，分成小块到样本库中寻找最匹配的高分辨率块，然后复原出高分辨率图象。-Superresolution recovery (into 1024) for a sample of high-resolution images and low-resolution images, respectively do block, when the new importation of a low-resolution image, divided into small samples to find the most matching high-resolution block, and then recover from high-resolution images. Platform: |
Size: 3072 |
Author:丽仙 |
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Description: S变换是较新的时频分析工具，甩在低频段有较宽的的时间窗，以获得较高的频率分辨率；而在高频段时间窗窄，以获得较高的时间分辨率。这里给出了ST和GST（广义S变换）的函数。-S transform is a relatively new time-frequency analysis tool, left in the low frequency band has a wide time window in order to obtain higher frequency resolution and in high-frequency narrow time window in order to obtain higher temporal resolution. Here are given ST and GST (generalized S transform) function. Platform: |
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Author:songzy41 |
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Description: 该程序是对在高分辨率和低擦地角的情况下，海面和地面的回波幅度服从对数正态分布的杂波进行仿真-The program is shining in the high-resolution and low angle, the surface and ground echo amplitude obey lognormal distribution of the clutter simulation Platform: |
Size: 1024 |
Author:zhen |
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Description: 利用小波双线性超分辨率重建算法得到的重建图像会出现低、高频系数不匹配的现象，从而使得到的高分辨率图像灰度偏移。本文对该方法进行了改进，并引入局部适应插值得到更为理想的重建算法。即小波与局部适应插值结合算法。-Using Wavelet bilinear super-resolution reconstruction algorithm is the reconstructed image will appear low, high-frequency coefficients does not match the phenomenon, thereby enabling high-resolution image to be offset. In this paper, the method is improved, and the introduction of local interpolation to be better adapted to the reconstruction algorithm. That is, wavelet interpolation combined with the local adaptation algorithm. Platform: |
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Author:wangjikui |
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Description: 基于多帧图像插值（Interpolation）技术的方法是SR恢复技术当中最直观
的方法。这类方法首先估计各帧图像之间的相对运动信息，获得HR图像在非均
匀间距采样点上的象素值，接着通过非均匀插值得到HR栅格上的象素值，最后
采用图像恢复技术来去除模糊和降低噪声（运动估计!非均匀插值!去模糊和
噪声）。-In this paper, we propose a novel method for solv-
ing single-image super-resolution problems. Given a
low-resolution image as input, we recover its high-
resolution counterpart using a set of training exam-
ples. While this formulation resembles other learning-
based methods for super-resolution, our method has
been inspired by recent manifold learning methods, par-
ticularly locally linear embedding (LLE). Speci?cally,
small image patches in the low- and high-resolution
images form manifolds with similar local geometry in
two distinct feature spaces. As in LLE, local geometry
is characterized by how a feature vector correspond-
ing to a patch can be reconstructed by its neighbors
in the feature space. Besides using the training image
pairs to estimate the high-resolution embedding, we
also enforce local compatibility and smoothness con-
straints between patches in the target high-resolution
image through overlapping. Experiments show that our
method is very ?exible Platform: |
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Author:qianyeyu |
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Description: 基于视频的超分辨率重建是指从许多帧连续的低分辨率图像中重建出一幅高分辨率的图像，并且这幅高分辨率的图像能够显示出单帧低分辨率图像中丢掉的细节(Super-resolution reconstruction based on video refers to the reconstruction of a high resolution image from a number of consecutive low resolution images, and this high resolution image can display the details lost in a single frame low resolution image.) Platform: |
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Author:联考 |
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Search - low and high resolution in matlab