Exercise2

matlab傅立叶变化实现高通或者低通滤波(matlab fourier changes to achieve high-pass or low pass filter)

Hilbert Huang Transform 绝对可用 性能超强哦:)(Hilbert Huang Transform absolute performance super available Oh:))

Lattice based RLS Algorithms using matlab with examples

基于遗传算法的公交排班系统分析,很好的运用在公交排班上(Analysis of bus scheduling system based on genetic algorithm)

在matlab环境下，实现用Ｂ样条函数构造小波函数的源程序，经仿真，正确(In the matlab environment, using B-spline function of the source wavelet function constructed by the simulation, the correct)

matlab中AR模型功率谱估计中AR阶次的实现(matlab power spectral estimation of AR model order of the realization of the AR)

File with compression factor of the particle swarm algorithm, the weight to improve particle swarm optimization, adaptive weighting method, the random weighting method, particle swarm optimization variable learning factor, learning factor of asynchronous change, the second-order particle swarm optimization, second-order oscillating particle swarm algorithm, chaotic particle swarm optimization, hybrid particle swarm optimization, hybrid particle swarm optimization, simulated annealing algorithm

振动理论中的主动控制程序，对于振动方面的学习有一定的帮助。(The active control of vibration theory program, the vibration aspects of learning have some help.)

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：  该算法实现了宽带麦克风阵列的波束形成，主要采用了频域DFT和时域FIR波束形成器(The algorithm for broadband microphone array beam-forming, the main frequency domain using DFT and time-domain FIR Beamformer)