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ga

于 2009-05-24 发布 文件大小:5KB
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说明:  基于遗传算法的寻优的matlab程序源代码(Based on genetic algorithm optimization matlab source code)

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    给出了信号压缩通常的变换-量化-编码函数。DHT函数为离散DHT变换,是FFT变换的近似,其正反变换相同,克服了FFT复系数不利于存储的缺点。LLMAX函数给出了某x序列在固定比特下的最佳量化输出。熵编码函数为霍夫曼编码。(Gives the signal compression usually transform- quantitative- coding function. DHT DHT discrete transform function, the FFT transform approximation, the same positive and negative transformation, overcoming complex FFT coefficient is not conducive to storage shortcomings. LLMAX function x is given a fixed bit sequence in the optimum quantized output. Entropy coding function as Huffman coding.)
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  • mat2huff-bianma-
    使用mat2huff进行编码,进一步说明霍夫曼编码的压缩性能!显示其压缩比例,以及其图像的对比!(Encoded using mat2huff to further clarify the Huffman coding compression performance! Shows the compression ratio and the image contrast!)
    2011-05-22 11:04:59下载
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  • bianshengchuli
    1 录入一段语音,对其进行时域频域处理,通过变频、变速达到变声目的,且使处理后的语音信号不影响正常收听与理解。 2 用图形用户界面(GUI)对上述变声前变声后进行时域频域图形输出,不同的频率、速度有不同的输出,且对前后波形进行比较 (1 entry a voice, the frequency domain and time domain by frequency conversion variable speed, processing to make the treatment and voice purpose, after the speech signal shall not affect the normal to listen to and understand. 2 with the graphical user interface (GUI) voice of the above voice before after the frequency domain in the time domain graphics output, different frequency, speed have different output, and compared before and after waveform )
    2021-03-30 16:49:10下载
    积分:1
  • LZ78Encode
    信息论与编码中LZ系列LZ78编码源文件(LZ series of information theory and coding LZ78 encoding the source file)
    2012-07-01 17:11:19下载
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    LMS adaptive fulter in matlab. for remove echo in telecomunication
    2013-10-07 19:56:39下载
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    压缩感知的信号恢复算法集合,包括ISD_v1.1,l1magic-1.1和sparsify_0_5(Compressed sensing signal recovery algorithms collections, including ISD_v1.1, l1magic-1.1 and sparsify_0_5)
    2013-03-19 10:56:08下载
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    2013-08-09 16:24:26下载
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  • xinhaoxishubiaoshi
    信号稀疏表示是一种新兴的信号分析和综合方法,其目的就是在过完备字典中用尽可能少的原子来表示信号。采用时频原子字典的信号稀疏表示能够有效地揭示非平稳信号的时变特征。信号稀疏表示吸引了研究者的大量关注,这种方法已经被应用到信号处理的许多方面,例如非平稳信号分析,信号编码、识别与信号去噪等。(Signal sparse representation is a new method of signal analysis and synthesis, and its purpose is in over-complete dictionary of atoms using as little as possible to represent the signal. When using frequency atom dictionary signal sparse representation can effectively reveal the time-varying characteristics of non-stationary signals. Signal sparse representation attracted a lot of attention of researchers, this method has been applied to many aspects of signal processing, such as non-stationary signal analysis, signal encoding, recognition and signal denoising.)
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