adaptive training 中文意思是什麼
adaptive training
解釋
適應訓練-
Compared with the classical bp algorithm, robust adaptive bp algorithm possesses some advantages as following : ( 1 ) increasing the accuracy of the network training by means of using both the relative and absolute residual to adjust the weight values ; ( 2 ) improve the robustness and the network convergence rate through combining with the robust statistic technique by way of judging the values of the samples " relative residual to establish the energy function so that can suppress the effect on network training because of the samples with high noise disturbances ; ( 3 ) prevent entrapping into the local minima area and obtain the global optimal result owing to setting the learning rate to be the function of the errors and the error gradients when network is trained. the learning rate of the weights update change with the error values of the network adaptively so that can easily get rid of the disadvantage of the classical bp algorithm that is liable to entrap into the local minima areas
與基本bp演算法相比，本文提出的魯棒自適應bp演算法具有以下優點： （ 1 ）與魯棒統計技術相結合，通過訓練樣本相對偏差的大小，確定不同訓練樣本對能量函數的貢獻，來抑制含高噪聲干擾樣本對網路訓練的不良影響，從而增強訓練的魯棒性，提高網路訓練的收斂速度； （ 2 ）採用相對偏差和絕對偏差兩種偏差形式對權值進行調整，提高了網路的訓練精度； （ 3 ）在採用梯度下降演算法對權值進行調整的基礎上，通過將學習速率設為訓練誤差及誤差梯度的特殊函數，使學習速率依賴于網路訓練時誤差瞬時的變化而自適應的改變，從而可以克服基本bp演算法容易陷入局部極小區域的弊端，使訓練過程能夠很快的「跳出」局部極小區域而達到全局最優。 -
Traditional multiuser detector make good use of all signals which resuilt in multiple access interference so that it provides optimum mai resistance. ( 1 ) nevertheless, it assumes that the receiver can acquire the signature waveform and timing of desired user and the interfering users ; ( 2 ) it has no ability to suppress intercell multiple access interference ; ( 3 ) it cannot be applied in downlink channels. adaptive multiuser detector eliminates the need to know the signature waveforms and the timing of the interferes and has to need training data sequences for every active user
傳統多用戶檢測在單用戶檢測技術基礎上，充分利用造成多址干擾的所有用戶的信息進行聯合檢測，從而具有良好的抗多址干擾能力，但存在一些缺陷： （ 1 ）不僅要求知道期望用戶的地址pn碼及其定時信息，還要求其他干擾用戶的地址pn碼及其定時信息； （ 2 ）不能消除其他相鄰小區的多址干擾對本小區的影響； （ 3 ）不能直接應用在cdma移動通信系統中的下行鏈路。 -
But the frequent use of training sequence is certainly a waste of channel bandwidth. research shows that with the prior knowledge of only the signature waveform and timing of the user of interest, blind adaptive multiuser detector can effectively detect data symbol of the desired user without training data sequence for every active user
在傳統多用戶檢測技術基礎上，自適應多用戶檢測利用訓練序列在僅知道期望用戶地址pn碼及其定時信息條件下就可以進行檢測，不足的就是訓練序列佔用了額外的頻率資源。 -
Periodic training sequence is essential for the conventional adaptive equalizers to combat the isi, but it wastes plenty of bandwidth
採用傳統的自適應均衡技術抑制碼間干擾，需要重復發送訓練序列，佔用大量本不富裕的帶寬。 -
Evidence suggests that the prognostic ability of the new model with high stability, when hidden nodes changing nearby input nodes and training times changing at the certain extent, is significantly better than traditional step wise regression model mainly due to the new model condensing the more forecasting information, properly utilizing the ability of ann self - adaptive learning and nonlinear mapping. but the linear regression technique only selects several predictors by the f value, many predictors information with high relative coefficients is not included. so the new model proposed in this paper is effective and is of a very good prospect in the atmospheric sciences fields
進一步深入分析研究發現，本文提出的這種基於主成分的神經網路預報模型，預報精度明顯高於傳統的逐步回歸方法，其主要原因是這種新的預報模型集中了眾多預報因子的預報信息，並有效地利用了人工神經網路方法的自組織和自適應的非線性映射能力；而傳統的逐步回歸方法是一種線性方法，並且逐步回歸方法只是根據f值大小從眾多預報因子中選取幾個預報因子，其餘預報因子的預報信息被舍棄。 -
The multistage constant modulus ( cm ) array is a cascade adaptive beamforming system that can recover several narrowband co - channel signals without training. the main idea of the smi - cma is to use smi to determine the initial weight for cma operation. the method can come up with the desire signal in despite of the interfering signal is stronger than the desire signal
基於以上考慮，我們提出了基於smi - cma聯合自適應方法，該演算法可以分離多個同通道信源，由smi演算法決定cma演算法的初始權向量，在干擾信號較強時，仍有穩定的sinr輸出，具有較快的收斂速度。 -
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。 -
Adaptive learning bp algorithm and weight decay method are applied to training network
採用weightdecaymethod訓練網路，起到修剪網路結構的作用，促使權向小的方向變化。 -
To overcome the defect of the adaptive equalizers, this thesis deal with the technique of the blind equalization that need not the training period
針對傳統的通道均衡技術的缺陷，本論文研究了不需要訓練碼就能直接進行通道均衡的盲均衡技術。 -
Exponentially weighted moving average ( ewma ) and fuzzy algorithm for the input samples are also developed to improve its recognition accuracy. numerical simulation results show this model possesses many advantages, such as good self - adaptive ability, quick training and good recognition performance
文中提出了採用歐氏距離判別法作為混合型多特徵異常模式的識別方法；提出了採用數據模糊化和指數加權滑動平均處理兩種提高模型識別精度的方法。 -
In the training process, the adaptive learning rate and error batch - mode process are introduced to accelerate the training rate
在神經網路自學習過程中，引入了自適應學習速率和誤差批處理法，加快了學習速度。 -
This study suggests that children with mr have great potential to develop adaptive skills. during the education and training for them, what is crucial is to develop their independant and social skills and what is difficult is to develop the cognitive skills, especially the ability of language. moreover it is needed to make individual program according to the character of every child
以上的研究結果表明，弱智兒童適應行為的發展存在著巨大的潛力，對他們的教育與訓練應以獨立技能和社會技能的發展為重點，以認知技能特別是言語能力的發展為難點，並要根據每個兒童的特點進行個別化教學。 -
Different training algorithms, namely levenburg - marquart algorithm and the gradient - based algorithm with an adaptive learning rate and momentum, are compared in this paper. according to the engineering requirement, dimensions of idc can be designed using the trained ann model and ga
將自適應調整學習率並加入動量因子的梯度下降法和levengurg - marquart訓練演算法的訓練結果做了比較分析，同時引入了性能函數的改進形式。 -
This method utilizes an on - line algorithm based upon lssvm ( least square support vector machine ), which can build adaptive models to predict the cod values of unknown water samples quickly and accurately. in the modeling process, every training sample is also assigned a prior weight to take their significance to the final predictive model into account
該方法是一種基於最小二乘支持向量機的在線自適應加權演算法，這種演算法可以自適應地選取和未知水樣最相近的標準樣本進行建模，同時在建模中又利用加權的方法分別考慮了各個標準樣本重要性。 -
Compared with conventional tracking methods, the detector is a stronger observation model due to its discriminative power gained by training over large data sets, which makes it more adaptive to image changes ; meanwhile, this built - in detector also equips the tracking framework with auto - initialization and the ability to quickly discover new targets
另一方面，與逐幀檢測相比，基於檢測的跟蹤利用了物體運動在時序上的連續性，因此速度更快；且由於時序上檢測信息的融合使輸出更平滑，降低了誤報和漏檢。 -
The adaptive predistorter given can achieve the predistortion compensation based on piecewise estimating hpa nonlinear characteristic curve and training hpa estimator nonlinear parameters via performing inverse transform with curve fitting section by section
自適應預失真器是基於對大功率放大器的非線性特性進行分段估計，由曲線擬合逐段取逆變換來訓練大功率放大器的預失真器的非線性參數，以達到預失真補償的目的。 -
Based upon the deficiencies of the back propagation algorithm in the practical application, after some mechanisms effecting the network training and the other performances are analyzed when training samples with disturbance are employed in training, in this paper, through combining the chief thoughts of the classical bp algorithm and the robust statistic technique, improving the optimal algorithm of the bp algorithm, a new algorithm with high robustness - robust adaptive bp algorithm is proposed, and also make a good effect when integrated this new algorithm with the dynamical bp network to predict the stock price
本文從基本bp演算法在應用中存在的不足出發，著重分析了訓練樣本中所含噪聲對基本bp演算法在網路訓練過程中產生的不良影響，並以此為依據，採用魯棒統計技術，同時在優化演算法上做了一些有益的改進，提出一種新的具有較強抗干擾能力的bp演算法? ?魯棒自適應bp演算法，並將其應用於動態bp網路，進行股票價格的預測，取得了較好的預測效果。 -
For the children with mental retardation the impairment in intelligence is unchangable, but the impairment in adaptive behavior can be improved by training
對於弱智兒童而言，其智力的損傷是不可改變的，而適應行為的損傷卻可以通過訓練得到補償，所以對弱智兒童訓練的重點應放在適應行為訓練上。 -
Instead of fix grids, adaptive grids derived from the pixel projection histograms are employed. the proposed system ensembles multiple classifiers based on boosting algorithm. this integrated classifier works in a similar way to the serial integration mode in the training stage, and to the parallel integration mode in the classification stage
實驗基礎上，本文從全局特徵集、紋理特徵集中選取分類能力強的特徵分量集；並改進網格的選取方案，採用基於像素投影直方圖的自適應網格劃分，以處理用戶簽名的多變性。 -
Then we establish the system model and make the simulation experiments. it is shown that the performance of the algorithm is better than that of the conventional rake receiver combining the same number of multipath components and approaches that of an adaptive receiver in the decision - directed following training
建立了改進演算法的系統模型，進行了模擬實驗，結果表明mlccma演算法比採用合併多徑成分的傳統rake接收機的性能優越，而接近於使用學習序列的直接判決演算法的自適應接收機的性能。
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