枫树
发表于 2025-3-23 12:48:28
https://doi.org/10.1007/3-540-32986-2he relationship between the data and the decision is complex and/or the amount of data to transmit is large (e.g. in biologgers). Artificial Neural Networks (ANNs) can efficiently detect patterns in the input data which makes them suitable for decision making or compression of information for data t
Conjuction
发表于 2025-3-23 14:54:31
Kontrastmittel und Pharmakologie on the QR decomposition. The paper describes mathematical background that needs to be considered during the application of the scaled Givens rotations in neural networks training. The paper concludes with sample simulation results.
热情的我
发表于 2025-3-23 22:02:59
Durchleuchtung und Subtraktionsangiographieethod converges relatively slowly. In this paper a new approach to the backpropagation algorithm is presented. The proposed solution speeds up the BP method by using vector calculations. This modification of the BP algorithm was tested on a few standard examples. The obtained performance of both met
本能
发表于 2025-3-23 23:32:05
Konventionelle Röntgendiagnostikecently as a way of improving randomized learning of FNNs by adjusting the network parameters to the target function fluctuations. The method employs logistic sigmoid activation functions for hidden nodes. In this study, we introduce other activation functions, such as bipolar sigmoid, sine function
frenzy
发表于 2025-3-24 02:31:14
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alabaster
发表于 2025-3-24 09:15:45
Kontrastmittel und Pharmakologieons within signal and image processing, engineering, biomedicine, analysis of economic time series, etc. We are interested in estimating trend under the presence of heteroscedastic errors in the model. So far, there seem no available studies of the performance of robust neural networks or the taut s
TAG
发表于 2025-3-24 14:35:14
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allude
发表于 2025-3-24 17:45:48
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高脚酒杯
发表于 2025-3-24 20:04:42
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TRAWL
发表于 2025-3-25 01:47:54
https://doi.org/10.1007/978-3-662-43713-1ls are the research area of many practitioners and theorists. The article aims at examining the impact of settings of various neural network parameters on the results of currency forecasts. The three currency pairs the US dollar, British pound, and Swiss franc to EUR were selected for the analysis.