隱過程參數 的英文怎麼說

中文拼音 [yǐnguòchéngshēnshǔ]
隱過程參數 英文
implicit procedure parameter
  • 隱 : Ⅰ動詞（隱瞞; 隱藏） hide; conceal Ⅱ形容詞1 （隱藏不露） hidden from view; concealed 2 （潛伏的; ...
  • 過 : 過Ⅰ動詞[口語] （超越） go beyond the limit; undue; excessiveⅡ名詞（姓氏） a surname
  • 程 : 名詞1 （規章; 法式） rule; regulation 2 （進度; 程序） order; procedure 3 （路途; 一段路） journe...
  • 參 : 參構詞成分。
  • 數 : 數副詞（屢次） frequently; repeatedly
  • 過程 : process; procedure; transversion; plication; course
  1. This thesis tries to update the cmdsr system to achieve the characters below : real - time, better robust, higher recognition rate, non - special - man. considering the disadvantages of traditional improved spectrum subtraction speech enhancement, this thesis proposes the theory of fuzzy spectrum subtraction based on the fuzzy theory and improved spectrum subtraction speech enhancement ; as for the difficulties of detecting the endpoint of speech signal, the thesis gives the table of initial and the improved parameters, with which we can confirm the endpoints of mandarin digit speech ; the thesis puts forward two - level digit real - time speech recognition system, the first level is based on discrete hidden markov model which is linear predictive coding cepstrum ( lpcc ) and difference linear predictive coding cepstrum ( dlpcc ), the second level is based on formant parameters ; as for the realization of hardware, the thesis depicts the realization of every part of cmdsr based on the tms320vc5402 in detail ; as for the development of software, the thesis gives the software design flow chart of cmdsr, simulates the basic theory with matlab language and gives the simulation results

    針對傳統的「改進譜相減法語音增強」參數設定單一、環境適應能力差的缺點，提出了一種利用模糊理論和「改進的譜相減法」結合的「模糊譜相減法語音增強」 ;針對語音信號端點檢測困難的特點，通過matlab模擬試驗，給出了能夠準確確定數碼語音端點的初始和改進參數表;提出了利用基於線性預測編碼倒譜參數和差分線性預測編碼倒譜參數相結合的離散隱含馬爾可夫模型進行第一級識別、利用共振峰參數進行第二級識別的兩級漢語數碼語音識別系統，在保證系統實時性的同時，實現連接漢語數碼語音識別系統識別率的提高;在硬體實現上，詳細闡述了基於tms320vc5402的連接漢語數碼語音識別系統各部分硬體設計;在軟體開發上，給出了連接漢語數碼語音識別的軟體設計各部分的流程圖，並對各部分進行了matlab模擬，並給出了模擬結果。
  2. Firstly, influence factors of generalization of neural network are presented in this thesis, in order to improve neural network ’ s generalization ability and dynamic knowledge acquirement adaptive ability, a structure auto - adaptive neural network new model based on genetic algorithm is proposed to optimize structure parameter of nn including hidden layer nodes, training epochs, initial weights, and so on ; secondly, through establishing integrating neural network and introducing data fusion technique, the integrality and precision of acquired knowledge is greatly improved. then aiming at the incompleteness and uncertainty problem consisting in the process of knowledge acquirement, knowledge acquirement method based on rough sets is explored to fulfill the rule extraction for intelligent diagnosis expert system, by completing missing value data and eliminating unnecessary attributes, discretization of continuous attribute, reducing redundancy, extracting rules in this thesis. finally, rough sets theory and neural network are combined to form rnn ( rough neural network ) model for acquiring knowledge, in which rough sets theory is employed to carry out some preprocessing and neural network is acted as one role of dynamic knowledge acquirement, and rnn can improve the speed and quality of knowledge acquirement greatly

    本文首先討論了影響神經網路的泛化能力的因素，提出了一種新的結構自適應神經網路學習演算法，在新方法中，採用了遺傳演算法對神經網路的結構參數（隱層節點數、訓練精度、初始權值）進行優化，大大提高了神經網路的泛化能力和知識動態獲取自適應能力;其次，構造集成神經網路，引入數據融合演算法，實現了基於集成神經網路的融合診斷，有效地提高了知識獲取的全面性、完善性及精度;然後，針對知識獲取過程中所存在的不確定性、不完備性等問題，探討了運用粗糙集理論的知識獲取方法，通過缺損數據補齊、連續數據的離散、沖突消除、冗餘信息約簡、知識規則抽取等一系列的演算法實現了智能診斷的知識規則獲取;最後，將粗糙集理論與神經網路相結合，研究了粗糙集-神經網路的知識獲取方法。
  3. Normal bp algorithm can be used in many fields and resolved many practical problems, however, normal bp algorithm has many limitations such as it ' s easy to fall into the local minimum in the course of convergence, its " convergent speed is very slow, the method which set the structural parameter and the operational parameter has n ' t be widely accepted, and so on

    標準bp演算法應用甚廣，解決了許多的實際問題，但同時它也存在著諸如在收斂過程中容易陷入局部最小點、收斂速度很慢以及網路的結構參數（隱層數、隱層單元）和運算參數（步長、非線性函數的選擇）等都尚無公認的理論指導等問題。
  4. The principle of the evaluation system is described in details, included : defining the layer numbers of hidden neurons, defining the processing unit numbers of hidden neurons, defining the train numbers and selecting original value ; input and output parameters determination etc. the bp net can study and story a lot of mapping relationship of input - output model, and need not mathematics describing of mapping relationship in advance

    論文詳細論述了評估系統的設計過程：隱層數的確定、隱層單元數的確定、訓練次數的確定、初始值的確定和輸入輸出參數的確定等。 bp網能學習和存貯大量的輸入-輸出模式映射關系，而無需事前揭示描述這種映射關系的數學方程，只需用足夠多的模式對對網路進行訓練即可。
  5. The influence to the training circle times with number of hiding layer node 、 learning rate etc are discussed during the course of samples training. by comprehensive analyses and comparing, the comparatively rational value is adopted to be network ' s parameters

    本文在制粉系統故障及其相關故障診斷樣本訓練過程中，分析了隱層節點數、學習率等因素對網路訓練速度的影響，為網路參數合理選取提供了依據。
  6. According to the theory of equivalent time, creep as a function of equivalent time is expressed. by fitting experimental data, parameters of creep in equivalent time field are obtained ; initial strain implicit solution of elastic creep equation in equivalent time field is derived

    根據等效時間理論，將徐變表示為等效時間的函數，通過擬合試驗數據，得出等效時間域彈性模量和徐變度公式的計算參數，推導了等效時間域的彈性徐變方程的初應變隱式解法。
  7. The effect of electric field in the polarizer in the research of laser induced damage was analyzed, and on the basis of it, low losses laser polarizer was designed. based on the analyses, temperature distribution of optical film layers irradiated by the laser pulse was calculated with the alternating direction - implicit technique. from the results, we adjusted the technique parameters

    分析了薄膜內電場分佈對輻射穩定性的影響，並在此基礎上，設計了低損耗的激光偏振膜；從溫度場設計的角度出發，利用交替方向隱式原理編制了膜層內溫度分佈數值計算程序，通過計算薄膜熱參數對膜層內溫度分佈的影響，對沉積工藝進行了相應的調整。
  8. This network can be summarized as follows : ( 1 ) about the networks " architecture, it is not fully connected but it uses selective connection between the units of two hidden layers. the number of these units is determined dynamically. ( 2 ) during the learning procedure, a new input - output clustering ( ioc ) method is adopted to select centers

    該網路主要有以下特點： （ 1 ）網路結構上，兩層隱層選擇性連接，隱層節點數在學習過程中動態確定； （ 2 ）學習規則上，提出一種同時考慮輸入輸出樣本信息的輸入一輸出聚類（ input - outputclustering ， ioc ）方法，且聚類中心的形狀參數自適應變化。
  9. Wavelet transformation of hidden markov processes and its parametric estimation

    隱馬爾可夫過程小波變換的參數估計
  10. Chapter four introduces the basic theories of continue hidden markov models ( chmm ). the new method of faults diagnosis based mixture density chmms directly by the vibration ar coefficients vectors of rotating machine is proposed, and then the dynamic patterns presented in run - up process of rotor machine are successfully recognized. at last compares the two faults diagnosis methods of dhmm and chmm, and points out the advantages and disadvantages of the two methods

    第四章：在連續隱markov模型（ chmm ）的基本理論基礎上，提出了直接利用振動信號ar系數特徵矢量序列建立混合密度chmm的故障診斷新方法，並對轉子升速過程的振動模式進行了成功的識別；對dhmm和chmm故障診斷方法進行了對比分析，指出dhmm方法具有演算法穩定、計算速度快、識別精度高等特點，對于chmm方法只要通過合理選擇特徵參數也能得到高的識別精度。
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