隨機學習模型 的英文怎麼說
中文拼音 [suíjīxuéxímóxíng]
隨機學習模型
英文
stochastic learning model- 隨 : Ⅰ動詞1 (跟; 跟隨) follow 2 (順從) comply with; adapt to 3 (任憑; 由著) let (sb do as he li...
- 機 : machineengine
- 學 : Ⅰ動詞1 (學習) study; learn 2 (模仿) imitate; mimic Ⅱ名詞1 (學問) learning; knowledge 2 (學...
- 模 : 模名詞1. (模子) mould; pattern; matrix 2. (姓氏) a surname
- 隨機 : random stochasticrandom
- 模型 : 1 (仿製實物) model; pattern 2 (制砂型的工具) mould; pattern3 (模子) model set; mould patter...
-
In rsdm, binary patterns are replaced by real - valued patterns, accordingly avoiding the coding process ; the outer learning rule is replaced by regression rule, therefore the model has not only the ability of pattern recognition but the ability of function approximation. the prearrangement of the address array bases on the distribution of patterns. if the distribution of patterns is uniform. then the address array is prearranged randomly, otherwise predisposed with the theory of genetic algorithm and the pruneing measure so as to indicate the distribution of patterns and improve the network performance. non - linear function approximation, time - series prediction and handwritten numeral recognition show that the modified model is effective and feasible
在rsdm中,以實值模式代替二值模式,避免了實值到二值的編碼過程:以回歸學習規則代替外積法,使該模型在具有識別能力的同時具有了對函數的逼近能力;地址矩陣的預置根據樣本的分佈採取不同方法,若樣本均勻分佈,則隨機預置,否則利用遺傳演算法的原理和消減措施來預置地址矩陣,使之反映樣本的分佈,改善網路的性能。2. the effect of xas on the impairment of learning and memory induced by chemical drugs in mice mice were randomly grouped into blank control, pattern group, piracetam group and xas groups
二、文冠果皂甙對化學藥物所致小鼠學習記憶障礙的影響將昆明種小鼠隨機分為空白對照組、模型組、腦復康組、文冠果皂甙不同劑量組。The kanerva ' s sparse distributed memory ( sdm ) tackles the problem of training large data patterns and extendes the storage mode of existing computer. but it ' s address array produced randomly ca n ' t reveal the distribution of patterns and it has ' t the ability of function approximation for its learning rule
Kanerva的稀疏分佈存儲( sdm )模型解決了大維數樣本的訓練問題,推廣了現有計算機的存儲方式。但其地址矩陣的隨機預置方式不能反映樣本的分佈,並且sdm的學習方式使之不能用於函數逼近及時間序列預測問題。The bp neural network is applied to the recognition of wear particles, and a bp neural network sorting system expected to recognize severe wear particle, cutting wear particle, normal wear particle and fatigue wear particle is designed and trained. 6. the function of the neural network ' s hidden layer is analyzed
將神經網路應用於磨粒識別,設計磨粒分類器,在網路學習中運用改進的bp模型,識別嚴重滑動磨損磨粒、切削磨粒、正常磨損磨粒和疲勞點蝕磨粒,隨機選取50個樣本對分類器進行訓練。With the development of simulation - technology and virtual reality, virtual prototype based on system simulation, flight dynamics, electronic technique, autocontrol theory and cad / cam has been more and more widely applied to the military rehearsal and the design and manufactural process of major weapon system
隨著模擬技術特別是虛擬現實技術的發展,以系統模擬、飛行動力學、電子技術、自動控制理論以及cad cam技術等為基礎的虛擬樣機技術在大型武器系統的研製以及軍事演習等方面的應用愈加的成熟起來。This paper studies a design method of decentralized signal detection system which consists of adaptive fuzzied local - detectors and a data fusion rule of on - line self - learning weights. the local - detectors for inaccurate signal parameters are modeled by means of fuzzy sets which can be adapted to change of the inaccurate signal parameteres. the data fusion center where the optimal declsion rules are used as objective function can learn the local decision weights on - line. the robustness of the fuzzied local - detectors and the adaptability of the self - learned fusion rule make it true that the detection performance of the decentralized detection system is improved under uncertainty and this system can also process the decentralized signal detection with a unknown parameter of unknown distribution or non - random unknown parameter
本文研究了一種由局部自適應模糊檢測器和在線自學習融合演算法所構成的分散式信號檢測系統的設計方法.由模糊集對不精確信號參數的局部檢測器進行建模,該模糊模型可自適應不精確信號參數的變化.融合中心以最佳融合規則作為目標函數在線自學習局部判決的權重.局部模糊檢測器的魯棒性和自學習融合演算法的自適應性使該分散式檢測系統在不確定環境下的檢測性能得到提高.也使該系統能夠處理未知分佈的未知參數以及非隨機未知參數的分散式信號檢測In this paper, an adaptive hidden markov model ( ahmm ) approach for on - line hand - drawn shape recognition is presented. in our method, hmms are chosen as the core recognizer due to its great ability to model stochastic time series. many improvements are made to the traditional hmm recognizer in order to increase the flexibility of the recognition system, the resulting framework can not only adaptively learn from training data, but also can adapt system behavior to input hand - drawn shape
本文提出了一種用於聯機手繪圖形的自適應隱馬爾科夫模型識別方法,該方法利用隱馬爾可夫模型( hmm )對時序隨機序列的描述能力作為手繪圖形識別中的核心分類器,並且在傳統hmm識別結構的基礎上進行了改進,使得識別系統不僅具有自適應學習訓練樣本的能力,而且具有根據輸入圖形特徵調節系統行為的能力。As a substitute of practices, virtual port practice basement system can produce the port work model, by which shows the complication of port work
虛擬港口實習基地系統作為代替生產的主要手段,首先應該能夠生成港口生產作業模型,體現出港口生產作業復雜性和隨機性的特點,為學生提供一個虛擬實習的平臺。The formalization of aesthetics feeling, value direction is also adapt to knowledge process of product design which is a field full of fuzzy, uncertain, dynamic and changing information. the paper also builds a web - based opening learning environment
並構建了基於internet的開放學習環境,研究了人腦模型與學習環境融合、設計師與學習環境融合的人機伴隨工作模式。分享友人