Results 41 to 50 of about 639,551 (228)

TeraHertz imaging of hidden paint layers on canvas

Optics Express, 2009
We show terahertz reflection images of hidden paint layers in a painting on canvas and compare the results with X-ray Radiography and In-frared Reflectography. Our terahertz measurements show strong reflections from both the canvas/paint interface and from the raw umber/lead white interface, indicating sufficient refractive-index contrast.
Adam, A.J.L. (author), Planken, P.C.M. (author), Meloni, S. (author), Dik, J. (author)   +3 more
openaire   +4 more sources

Motion-generation system for violin-playing robot using reinforcement learning differences in bowing parameters due to changes in learning conditions and sound pressure values

Frontiers in Robotics and AI
Recently, research on human-robot communication attracts many researchers. We believe that music is one of the important channel between human and robot, because it can convey emotional information. In this research, we focus on the violin performance by
Kenzo Horigome, Koji Shibuya
doaj   +1 more source

Deep Learning with Stacked Denoising Auto-Encoder for Short-Term Electric Load Forecasting

Energies, 2019
Accurate short-term electric load forecasting is significant for the smart grid. It can reduce electric power consumption and ensure the balance between power supply and demand.
Peng Liu, Peijun Zheng, Ziyu Chen
doaj   +1 more source

Storage capacity of correlated perceptrons

, 1996
We consider an ensemble of $K$ single-layer perceptrons exposed to random inputs and investigate the conditions under which the couplings of these perceptrons can be chosen such that prescribed correlations between the outputs occur.
A. Engel, A. Engel, A. Engel, A. Priel, B. Schottky, D. Malzahn, D. Saad, E. Barkai, E. Barkai, E. Gardner, G. Cybenko, G. J. Mitchison, I. Kanter, J. A. Hertz, M Biehl, M. Bouten, M. Bouten, M. Copelli, M. Griniasty, M. Griniasty, M. Opper, R. Monasson   +21 more
core   +1 more source

Correlations between hidden units in multilayer neural networks and replica symmetry breaking

, 1999
We consider feed-forward neural networks with one hidden layer, tree architecture and a fixed hidden-to-output Boolean function. Focusing on the saturation limit of the storage problem the influence of replica symmetry breaking on the distribution of ...
A. Engel, A. Engel, A. Engel, A. Priel, B. Schottky, D. J. Amit, D. Malzahn, D. Malzahn, E. Barkai, E. Barkai, E. Gardner, E. Gardner, E. Gardner, G. Györgyi, M. Griniasty, M. Mézard, M. Opper, P. Majer, R. Monasson, W. H. Press, W. Whyte   +20 more
core   +1 more source

Prediction of Flight Status of Logistics UAVs Based on an Information Entropy Radial Basis Function Neural Network

Sensors, 2021
Aiming at addressing the problems of short battery life, low payload and unmeasured load ratio of logistics Unmanned Aerial Vehicles (UAVs), the Radial Basis Function (RBF) neural network was trained with the flight data of logistics UAV from the ...
Qin Yang, Zhaofa Ye, Xuzheng Li, Daozhu Wei, Shunhua Chen, Zhirui Li   +5 more
doaj   +1 more source

Numerical Performance of the Fractional Direct Spreading Cholera Disease Model: An Artificial Neural Network Approach

Fractal and Fractional
The current investigation examines the numerical performance of the fractional-order endemic disease model based on the direct spreading of cholera by applying the neuro-computing Bayesian regularization (BR) neural network process.
Saadia Malik
doaj   +1 more source

Multilayered feed forward Artificial Neural Network model to predict the average summer-monsoon rainfall in India

, 2006
In the present research, possibility of predicting average summer-monsoon rainfall over India has been analyzed through Artificial Neural Network models.
A.J. Matthews, B. Men, B. Sivakumar, B. Sivakumar, B. Sivakumar, B. Widrow, B.G. Brown, C. Cartalis, C. Varotsos, C. Varotsos, C. Varotsos, C.P. Jacovides, D.S. Wilks, D.S. Wilks, E.H. Chin, J.B. Elsner, J.M. Gregory, K.Y. Kondratyev, K.Y. Kondratyev, L. Ferranti, M. Gevrey, M.J.C. Hu, M.W. Gardner, O.C. Clark, P. Guhathakurta, P. Perez, P. Perez, P.D. Sardeshmukh, P.R.C. Reddy, S. Gadgil, S. Haykin, S. Lee, S.K. Pal, S.M.S. Nagendra, S.V. Kamarthi, S.V. Kartalopoulos, Surajit Chattopadhyay, T. Shinoda, T.J. Sejnowski, T.M. Smith, W.W. Hsieh   +40 more
core   +1 more source

A Single Hidden Layer Feedforward Network with Only One Neuron in the Hidden Layer Can Approximate Any Univariate Function [PDF]

Neural Computation, 2016
The possibility of approximating a continuous function on a compact subset of the real line by a feedforward single hidden layer neural network with a sigmoidal activation function has been studied in many papers. Such networks can approximate an arbitrary continuous function provided that an unlimited number of neurons in a hidden layer is permitted ...
Guliyev, Namig, Ismailov, Vugar
openaire   +4 more sources

Estimation of tomato drying parameters using artificial neural networks [PDF]

Pizhūhish va Nuāvarī dar ̒Ulūm va Sanāyi̒-i Ghaz̠āyī, 2012
In this research we have simulated drying tomato thin layer by hot air convection. Tomato slices were dried in two temperatures 60° and 70℃. Perceptron neural network was used to predict moisture ratio and drying rate of samples during the drying process.
M. Mokhtarian, F. Koushki
doaj   +1 more source