canonical processing 中文意思是什麼
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Lpc prediction error ; one - side autocorrelation sequence lpc ; acoustic front end processing ; canonical correlation based on compensation ; combination of features
線性預測誤差單邊自相關線性預測語音前端聲學處理正則相關分析的譜變換補償特徵綜合 -
Firstly, a new joint filterbank precoders and decision feedback equalizers structure is proposed, and the corresponding optimization result based on the maximal mutual information criterion is derived. secondly, the concept of dt canonical model is proposed, which is very suitable for the task of blind signal processing based on the second - order statistical of the observations. thirdly, the methods of blind equalization and identification of the tv dispersive channels are researched systematically based on the proposed dt canonical model, and a subspace blind identification algorithm of the time - invariant channel matrix is developed
本文創新性的成果在於：提出了預編碼-判決反饋聯合均衡系統結構，並從理論推導得出了對應的最大互信息量最優化設計結果；首次提出了時變色散通道的離散正則模型概念，該模型適宜於利用觀察數據的二階統計量進行盲信號處理；基於離散正則模型對時變色散通道進行了系統的盲均衡和盲辨識方法研究，提出了對時不變通道矩陣的子空間盲辨識演算法；針對誤差傳播效應問題，提出了可以消除誤差傳播效應的兩級盲辨識演算法；提出了基於離散正則模型的直接盲均衡演算法；提出了基於特徵恢復思想的神經網路直接自適應盲均衡演算法。 -
We propose the joint filterbank precoders and decision feedback equalizers structure at first, by which the dispersive channel is equivallent into parallel independent flat fading subchannels such that the diversity gain of the receiver is increased. then we adopt the discrete - time ( dt ) canonical model to convert the problem of blind signal processing of tv dispersive channels into processing the time - invariant multi - channels model blindly, and discuss the problem of blind equalization and identification of tv dispersive channels based on this new model
第一種是採用濾波器組聯合均衡方法將色散通道等價為一組獨立的平坦衰落子通道，以提高接收機的分集增益；另外一種是提出採用離散正則模型將時變色散通道的盲信號處理轉化為時不變多通道模型的盲信號處理，並針對該模型對時變色散通道的盲均衡與盲辨識方法進行了詳細討論。 -
Non - canonical input processing will handle a fixed amount of characters per read, and allows for a character timer
非標準輸入處理可以用於需要每次讀取固定數量字元的情況下，並允許使用字元接收時間的定時器。 -
There are difficulties in noisy speech recognition, especially low signal - to - noise rations are more difficult. this paper describes briefly six methods for speaker - dependent noisy speech recognition isolated words. they are lpc prediction error method, one - side auto - correlation sequence lpc, acoustic front end processing, canonical correlation based on compensation method, combination of features method and increase of poles method. the experimental results show that all the six techniques can improve effectively noisy speech recognition, and the best noisy speech recognition rate is above 80 % when snr 0db
它們是：線性預測誤差法，單邊自相關線性預測法，語音前端聲學處理法，正則相關分析的譜變換補償方法，特徵綜合法和同模極點增加法。實驗結果表明，這6種方法都有效地提高了噪聲環境中語音識別率，其中較好的方法在強噪聲環境中信噪比為0db的語音識別率達到80 %以上，為信噪比較低的噪聲環境中自動語音識別展現了美好前景。 -
We also place emphasis on research of apriori and fp - growth algorithm and compare the performance of two algorithms. secondly, we do research on concepts of structured and nonstructured data, actual state and problems of tree structure mining, and freetreeminer algorithm theory. we also study canonical form and pre - processing technologies of free - tree, concepts and properties of closed and maximal tree, and pruning, growing and mining of tree structure
其次，研究了結構化與非結構化數據的基本概念、樹結構挖掘的研究現狀、現有樹結構挖掘技術存在的問題、 freetreeminer演算法及其基本思想，重點研究了free樹的規范化和預處理技術、封閉頻繁子樹和最大頻繁子樹的概念和性質、樹結構的剪枝和生長技術、樹結構的挖掘技術。
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