基于误差反向传播算法对图像进行压缩的工作已有很多。
There have been many techniques of image compression based upon back propagation arithmetic.
以三层误差反向传播算法(简称BP算法)进行数据处理。
对非线性系统神经网络控制器提出了一种改进的误差反向传播算法。
An improved Backward Error Propagation Algorithm used as neural network controllers to control a nonlinear system is presented in this paper.
提供了人工神经网络的一种算法-误差反向传播算法的数学推导方法及上机实现步骤。
This paper provided the deduction of an algorithm for artificial neural network - the error back-propagation learning algorithm and the procedure to carry it out on computer.
为了对环境质量进行综合评价，运用误差反向传播算法的人工神经网络方法建立了环境质量评价的B -P决策模型。
In order to evaluate environmental quality, this paper proposed the B-P decision model for environmental quality by using artificial neural network method.
利用神经网络的误差反向传播算法(BP算法)，结合告警、天气和工程设计几方面的数据资料建立了微波中继段告警分析预测模型。
By means of BP (error back propagation) artificial nerve network, with data from alarm, weather and engineering documents, microwave hop performance analysis and forecast model is established.
应用神经网络的误差反向传播算法(BP)和大量的实测数据样本训练出了能在线诊断四种加工状态的BP模型并成功地诊断了实际加工状态。
The BP algorithm of Artificial Neural Networks and lots of experimental samples were used in training the BP model which succeeded in diagnosing four kinds of operational status.
利用误差反向传播的改进算法对样本数据进行训练，并用另外的一些样本数据验证模型的应用效果。
Using the improved error backward propagation, the model is trained with stylebook data and validated its effect by other stylebook data.
在误差反向传播(BP)算法的基础上，针对其不足提出了多种改进算法。
Based on error back propagation (BP) arithmetic, many improvements are put forward because of its disadvantages.
然后对本授导算法中的信号正向传播与误差反向传播两个过程，以及其中的信号值推演、误差值推演进行了分析和阐述。
Then the algorithm of the Tutoring positive signal propagation and error back-propagation of two processes, and in which the signal value deduction, deduction for error analysis and elaboration.
将以误差反向传播为训练算法的前馈式人工神经网络（BP- ANN）首次用于中草药的裂解气相色谱谱图解析。
The potential utility of feed forward artificial neural network using the back propagation algorithm (BP-ANN), in interpreting pyrogram data from traditional Chinese medicine was discussed.
基于误差反向传播的机制，针对连续制造过程的预测与控制，提出多层神经网络的逐个样本学习算法。
A one-by-one learning algorithm for multi-layer neural network modelling is presented based on the back-propagation mechanism of network error.
方法用遗传算法（GA）优化误差反向传播（ BP） 算法，两者结合构成混合算法。
Methods To optimize error backward propagation algorithm by using generic algorithm, to combine these two methods together to create hybrid algorithm.
方法用遗传算法（GA）优化误差反向传播（ BP） 算法，两者结合构成混合算法。
Methods To optimize error backward propagation algorithm by using generic algorithm, to combine these two methods together to create hybrid algorithm.
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