In order to improve the training speed of multilayer feedforward neural networks (MLFNN), we propose and explore two new fast backpropagation (BP) algorith
Fast library element gray code generators without feedback and feedforward networksUS4937845 * 1988年8月1日 1990年6月26日 Plessey Electronic Systems Corp. Fast library element gray code generators without feedback and feedforward networks
The paper builds onA Neural Algorithm of Artistic Styleby Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge by training feedforward neural networks that apply artistic styles to images. After training, our feedforward networks can stylize imageshundreds of times fasterthan the optimization-base...
Li K, Huang G-B, Ge SS (2010) Fast construction of single hidden layer feedforward networks. In: Rozenberg G, Ba¨ck T, Kok JN (eds) Handbook of natural computing. Springer, Berlin, Mar 2010Fast Construction of Single-Hidden-Layer FeedforwardNetworks. Li K,Huang G-B,Ge S S. ...
We introduce a fast and high performance image subsampling method using feedforward artificial neural networks (FANNs). Our method employs a pattern matching technique to extract local edge information within the image, in order to select the FANN desired output values during the supervised training ...
Ashok Kumar Goel;Suresh C Saxenax; Surekha Bha-not.2006 A fast learning algorithm for training feedforward neural networks.International Journal ofSystems Science.2006.709-722Fast learning algorithm for training feedforward neural networks,” Int - Goel, Saxena, et al....
FeedForwardNetwork network = FeedForwardNetwork.loadFromTextFile( new File("dnn.txt"), new File("feature_transform") ); First file represents the network, second represents the input transformation. Second file contains two vectors. Each input vector is transformed by adding the first vector and...
Fast Feedforward Networks 28 Aug 2023 · Peter Belcak, Roger Wattenhofer · Edit social preview We break the linear link between the layer size and its inference cost by introducing the fast feedforward (FFF) architecture, a log-time alternative to feedforward networks. We demonstrate that FFFs...
The proposed VMD-FFNN method is tested using synthetic and simulated signals, and it is compared with other well-known methods based on convolutional and recurrent deep neuronal networks. Finally, the proposed method is assessed using lab measurements in order to shown its performance in a real-...
*This paper presents a novel fast algorithm for feedforward neural networks training. It is based on the Recursive Least Squares (RLS) method commonly used for designing adaptive filters. Besides, it utilizes two techniques of linear algebra, namely the orthogonal transformation method, called the ...