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contains reeedsolomon code for wireless complete systm

说明：  基于小波变换的阈值去噪，对含噪声图像进行阈值去噪(Threshold based on wavelet transform denoising of images with noise threshold denoising)

混沌直接扩频通信方法研究，混沌直接扩频通信方法研究(Direct spread spectrum communication method of chaos, chaotic spread spectrum communication method of direct)

提出了一种基于人类视觉系统和模糊隶属度函数的小波卫星图像融合新算法,利用小波域的人类视觉系 统经验模型,刻画图像的边缘、纹理及高亮区域, 采用模糊隶属度函数自适应地计算权系数, 在小波域上通过加权 平均实现了图像融合。(Proposed a new algorithm based on human visual system and the fuzzy membership function of the wavelet satellite image fusion using wavelet domain experience in the human visual system model, depicting the image of the edge, texture, and the highlighted area, the use of fuzzy membership function adaptively calculate the weight coefficients in the wavelet domain by the weighted average realized fusion.)

matlab radar code for periodic ambiguity

(2,1,3)卷积码编码，软判决译码；matlab语言编码；verilog语言译码；((2,1,3) convolutional code encoding, soft-decision decoding matlab coding verilog decoder )

Photos with people (e.g., family, friends, celebrities, etc.) are the major interest of users. Thus, with the exponentially growing photos, large-scale content-based face image retrieval is an enabling technology for many emerging applications. In this work, we aim to utilize automatically detected human attributes that contain semantic cues of the face photos to improve contentbased face retrieval by constructing semantic codewords for efficient large-scale face retrieval. By leveraging human attributes in a scalable and systematic framework, we propose two orthogonal methods named attribute-enhanced sparse coding and attributeembedded inverted indexing to improve the face retrieval in the offline and online stages. We investigate the effectiveness of different attributes and vital factors essential for face retrieval. Experimenting on two public datasets, the results show that theproposed methods can achieve up to 43.5 relative improvement in MAP compared to the existing methods.

说明：  用于信号的分解、降噪和重构，实现故障诊断(Used for signal decomposition, noise reduction and reconstruction to realize fault diagnosis)

image compression with neural network

(7,3) rs code bit error probability simulation