輸出神經元 的英文怎麼說
中文拼音 [shūchūshénjīngyuán]
輸出神經元
英文
output neuron- 輸 : Ⅰ動詞1 (運輸; 運送) transport; convey 2 [書面語] (捐獻) contribute money; donate 3 (失敗) l...
- 神 : Ⅰ名詞1 (神靈) god; deity; divinity 2 (精神; 精力) spirit; mind 3 (神氣; 神情) expression; l...
- 經 : 經動詞[紡織] (把紡好的紗或線梳整成經紗或經線) warp
- 輸出 : 1 (從內部送到外部) export 2 [電學] output; outcome; outlet; out fan; fanout; 輸出變壓器 output ...
- 神經 : nerve; nervus
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We deduce frondose algorithm of three layers bp neural networks which is used in common, and discuss several important issues in designing neural networks which is used to forecast, for example, number of hidden layer, nerve cell number of hidden layer, epoch of learning, embryonic power value, decision of node number about input and outputo at the same time, this dissertation sums up things that conventional bp algorithm is improved on considering disadvantages of it
3推導了常用的三層bp神經網路具體演算法,討論了實際預測應用中神經網路設計方面的幾個重要問題,如隱層數、隱層神經元數、訓練次數、初始權值、輸入節點數以及輸出節點數的確定。同時,針對傳統bp演算法存在的各種各樣的缺點,文中綜述了對其改進的情況。Taking the advantage of the characteristic of nonlinear multi - zone partition in multi - dimension of mtn, an approach of employing mtn for archiving arbitrary digital logic was proposed. according to this approach, the xor operation which needs three stns to achieve was implemented using single mtn
然後對多閾值神經元及其輸出特性作了詳細分析,利用多閾值神經元具有在多維空間中多區域非線性劃分的特點,提出了用一個多閾值神經元實現任意數字邏輯的規范方法。A team of investigators reports in the may 24 issue of the journal neuron that the parts of the brain that respond to the prospects of winning and losing money while gambling are the same as those that appear to respond to cocaine and morphine
調查人員在5月24日出版的《神經元》雜志上發表了他們的研究報告,報告稱大腦中對賭博時贏錢和輸錢作出反應的部位和對可卡因和嗎啡作出反應的部位是同一部位。These data indicate that gabaergic inhibition makes an important contribution to the direction - dependent frequency tuning of most ic neurons. corticofugal modulation of the excitatory and inhibitory ftcs of most ic neurons was more pronounced at one sound direction than the other. sound direction effects on frequency tuning characteristics may undergo a postnatal development due to the development of excitation and inhibition integration
通過對幼年(出生后第四周)和成年蝙蝠下丘聽神經元頻率調諧的方向敏感性的比較,發現幼年蝙蝠頻率調諧的方向敏感性比成年蝙蝠差,並認為可能是動物發育過程中,下丘的興奮性和抑制性輸入的整合也有一個發育的過程。The fuzzy layer of the hybrid fnn include two kinds of neurons, one is gaussian fuzzification neuron which used to give the continuous input an fuzzy membership value, another is a presented fuzzy cluster neuron which also used to give the discrete input an fuzzy membership value
該混合模糊神經網路的模糊化層除了具有模糊化神經元,還加入一類模糊聚類神經元。模糊聚類神經元通過預先計算的模糊聚類隸屬度矩陣來輸出對應于離散輸入的模糊化值。A potential new drug, for example, could " help the neuron to keep extruding sodium so it can help the sodium - calcium exchanger get rid of calcium, thereby not allowing calcium to reach toxic leels, " on gersdorff said
比如說有一種藥可以幫助神經元泵出鈉離子從而幫助鈉鈣交換器運輸鈣離子,阻止鈣離子達到神經毒性濃度。In order to improve generalization capability of feedforward neural networks, the convinced networks generalization domain should be guaranteed to be close to networks input domain as maximal intrinsic error of networks output and maximal samples error are reduced by increasing hidden neurons in number in the progress of networks learning, otherwise generalization capability of feedforward neural networks is likely to be decreased
為了提高網路的泛化性能,從理論上分析指出,在網路學習過程中通過增加隱含層神經元來降低網路最大固有誤差和最大樣本誤差的同時,要求確保網路泛化定義域盡可能接近網路輸入定義域,否則將有可能降低網路的泛化性能。By the network, a optional nonlinear input - output mapping relationship can be realized. concrete mapping relationship materialize at the distributed linking weight values between neurons that build up the ann. due to the strong self - adaptability and self - learning - ability as well as excellent and robustness and tolerance ability, it can not only replace many traditional algorithm which is very complicated and timeconsuming, but also, because the processing to information is more close to person ' s thought activity habit, it provides a new way for solving the prediction of nonlinear system and unknown model
通過這種網路能夠實現任意的非線性輸入輸出映射關系,具體的映射關系體現在構成網路的神經元之間的分佈連接權上,由於網路具有很強的自適應和學習能力以及魯棒性和容錯能力,它不僅可以替代許多復雜耗時的傳統演算法,並且由於它對信息的處理更加接近於人的思維活動習慣,為解決非線性系統模擬和未知模型的預測提供了新途徑。In course of training the network, the structure of the network has been analysed. using the nonlinear theory, the node of the hidden layer is ascertained. by comparing this method is very efficient
( 5 )在網路訓練過程中,對神經網路結構進行了分析,建立了計算輸出和理想輸出關系非線性方程組,依據非線性方程理論闡述設計變量、樣本數量和輸出層單元數量的關系,確定了隱層神經元的數量,經比較該方法很有效。The paper forms the three information measures into measure vector as the input of cmac - cerebellar model articulation controller neural network and proposes a method of edge detection based on information measures and cmac. the edge contours generated by this method is very legible. the method has a high runtime performance and improves the resistance to noise
本文將圖像的三個信息測度作為分量組成邊緣特徵的測度向量,作為小腦模型神經元網路? cmac的輸入,提出一種基於信息測度和cmac網路的邊緣檢測方法,用該法得到的邊緣輪廓清晰,實時性好,並且抗噪能力有明顯提高:將上述邊緣檢測方法應用於無人值守變電站,提出一種瓷瓶裂紋故障監控方案。To be concrete, the principle of the system is just like this. whether breakout occurs or not is judged by expert system using two kinds of knowledge : neural network and knowledge base
具體來說,本系統的原理就是將神經元網路的輸出和知識庫的知識輸入到專家系統中來,由專家系統來進行綜合評判,判斷是否會發生漏鋼事故。This paper describes a three - layer feedforward rough neural network which has four input rough neurons and ten input conventional neurons, five hidden rough neurons and one output rough neuron
本文給出了三層前向粗神經網路,輸入層由4個粗神經元和10個一般神經元組成,隱層和輸出層分別由5個、 1個粗神經元組成。Using this system, we have studied matrine - inhibittory effect and trifluoperation - neuroprotection effect in hippocampal slices, also discussed the mechanism of long - term potentiation using anesthetic rats. the experiment results showed that matrine can inhibit the hyperactivity induced by penicillin sodium in dosage by changing the relative parameters of field potential ; trifluoperation can alter ps change with the time, enhance the degree and the ratio of ps recovery, then minis the hypoxic injury ; high frequency stimulate can increase ps amplitude and epsp slope for long time, buildup the in / out function of nerve cells, and enhance synaptic plasticity
結果表明,苦參堿能夠劑量依賴性地抑制青霉素誘導的神經元順向信號傳導激活過程,使細胞外記錄到的場電位各個參數發生相應改變;三氟拉嗪可以改變ps的時相變化,提高ps的恢復程度和恢復率,減小了神經元因缺氧引起的不可逆損傷;高頻刺激( highfrequencystimulate , hfs )可以長時間的增強ps的幅度和epsp的斜率,進而增強神經元的輸入輸出功能,增加了突觸的可塑性。In this paper, to resolve the coupling phenomena between temperature and humidity in wood drying system, a bp neural network based pid controller is proposed and applied to wood drying system. the architecture and learning algorithm of the proposed controller is more simpler and the physical meanings of the input layer ' s neurons and output layer ' s neurons are explicit. based on predefined control rules and self - learning, the bp network changs the scaling integral and differential parameters, therefore is able to control the variants using classical pid control algorithms and at the same time, decoupling control is implemented as well during the control procedure
本文針對木材幹燥過程中溫、濕度耦合的現象,提出一種將新的基於bp神經網路的pid控制器應用於木材幹燥控制系統的方案,其結構和學習演算法相對簡單,輸入層和輸出層神經元物理意義明確;它根據設定的某一控制規律,通過網路的自學習,調整pid控制器的比例、積分和微分參數,從而利用經典的pid控制演算法得到相應各變量的控制量參與控制,並在該過程中實現解耦控制,而不用給定樣本信號進行在線的學習。This algorithm recovers the absence of the empiric in the case of the fixed - topology network and generates an optimal topology automatically. we end this chapter with some problems in the future. in chapter 2, we present an evolution strategy to infer fuzzy finite - state automaton, the fitness function of a generated automaton with respect to the set of examples of a fuzzy language, the representation of the transition and the output of the automaton and the simple mutation operators that work on these representations are given
目前,國內外對神經網路與自動機的結合的研究己取得了一系列成果;在第一章,我們首先將對這些結果以及這個領域的研究思想與方法做一個概要的介紹;然後提出一種推導模糊有限狀態自動機的構造性演算法,解決了模擬實驗中所給出的具體網路的隱藏層神經元個數的確定問題;在實驗中,我們首先將樣本輸入帶1個隱藏層神經元的反饋網路訓練, 150個紀元以後增加神經元,此時的新網路在124紀元時收斂;而blanco [ 3 ]的固定性網路學習好相同的樣本需要432個紀元。White noise acting as inspirit signal, the experiment data is collected. utilizing these data and error back propagating identification method, different neuron and input - output delay are selected. by comparing approximation ability and generalization ability, the neural networks model in position mode and velocity mode is identified
並以模擬白噪聲為激勵信號,收集了數據;利用實際收集的數據,採用誤差反傳的辨識方法,選擇不同神經元及輸入輸出延時量的模型,通過比較網路的逼近能力和泛化能力,辨識得到了位置和速度兩種工作模式下的方位通道的神經網路模型。The anterior pagoda neuron is one of the largest neurons in the leech nervous system. it receives multiple sensory inputs. the physiological function of ap is unknown. with the combination of intra - and extra - cellular electrophysiological recording methods, it is suggested that ap neuron modulates the membrane potential of multiple muscle cells in the contralateral body wall
水蛭前寶塔神經元ap是神經節前側囊中胞體最大的神經元,它接受多種感覺傳入,但傳出功能未知。通過應用細胞內外電生理學記錄結合方法,揭示了ap神經元的輸出效應可能是調制水蛭體壁肌肉細胞膜的興奮水平。Because the difference of real - valued and complex - valued system, the different neuromime is adopt in different system. in addition, this paper design two kinds of transmission function to different input signal. the new algorithm make up the flaw such as small application domain and difficult chose of parameter
文中針對實數和復數系統的差異提出了兩種不同的網路神經元結構,並且根據傳輸信號的差異設計了兩種傳輸函數,彌補了原來演算法應用范圍小、參數不易選取的缺陷。As far as the nonstationarity during the long period operation of machinery was concerned, the application of adaptive linear element ( adaline ) neural network to prediction of nonstationary time series was studied. the relationship between adaline and auto regressive ( ar ) model was analyzed, and the method to determine the number of input neurons in adaline prediction model according to bic criteria was presented. the effect of the adaptive learning rate on prediction was also analyzed
針對生產實踐中設備運行的非平穩性,基於動態預測思想,研究了非平穩時間序列的自適應線性單元( adaline )神經網路預測,討論了adaline和自回歸( ar )模型之間的關系,提出根據ar模型定階方法確定adaline預測模型的輸入神經元數目,分析了自適應學習率對預測性能的影響,為機械設備狀態預測提供了一種方法。The bic method generalized from ar model was adopted to determine the number of input neurons in grnn prediction model. the grnn was applied to single - step and multi - step ahead prediction of the vibration time series of a rotating machine, and its performance was compared with that of 3 - layers perceptrons network with error back propagation training algorithm ( bpnn ). it is indicated that the grnn is more appropriate for prediction of time series than the bpnn, and the performance of grnn is qualified even with sparse sample data
研究了基於廣義回歸神經網路( grnn )的大型旋轉機械振動狀態預測,提出了應用bic準則確定grnn預測模型輸入神經元數目的方法,將grnn用於大型機組振動峰?峰值時間序列的預測,與採用誤差反向傳播學習演算法的三層前饋感知器網路( bpnn )的預測結果對比表明, grnn的預測性能優于bpnn ,而且,即使樣本數據稀少,也能獲得滿意的預測結果。分享友人