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  • ICANN
  • This book includes the proceedings of the International Conference on Artificial Neural Networks (ICANN 2006) held on September 10-14, 2006 in Athens, Greece, with tutorials being presented on September 10, the main conference taking place during September 11-13 and accompanying workshops on perception, cognition and interaction held on September 14, 2006. (springer.com)
  • probabilistic
  • The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. (frontiersin.org)
  • Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. (frontiersin.org)
  • It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. (frontiersin.org)
  • The models mentioned above were all either explicitly probabilistic models or could be linked easily with probabilistic, Bayesian computations. (frontiersin.org)
  • On the other hand, Rumelhart and I diverged from the path of probabilistic Bayesian models, proposing a model of context effects in letter perception ( McClelland and Rumelhart, 1981 ) that did not refer explicitly to probabilistic Bayesian ideas, drawing inspiration, instead, from models of neural activation ( Grossberg, 1978 ). (frontiersin.org)
  • adaptive
  • Adaptive spike-time coding additionally allows for the dynamic control of neural coding precision: we show how a simple model of arousal in AdSNNsp further halves the average required firing rate and this notion naturally extends to other forms of attention. (rug.nl)
  • evolving paradigm
  • This evolving paradigm has gained much attention not only because there are situations where CVNNs are inevitably required or greatly effective than its counterpart, the real-valued neural network (RVNN), but because of its usefulness which is enshrined in the fundamental theorem of Algebra [ 25 - 27 ]. (hindawi.com)
  • algorithm
  • The-Anh Nguyen , Jun-Won An , Jae-Kwang Choi, Nam Kim , Seok-Hee Jeon, Young Soo Kwon, "Hybrid algorithm to reduce the computation time of genetic algorithm for designing binary phase holograms," Optical Engineering 43(9), (1 September 2004). (spiedigitallibrary.org)
  • approach
  • To reduce computation time, a new approach for designing computer-generated holograms is proposed. (spiedigitallibrary.org)
  • A new approach for determining the coefficients of a complex-valued autoregressive (CAR) and complex-valued autoregressive moving average (CARMA) model coefficients using complex-valued neural network (CVNN) technique is discussed in this paper. (hindawi.com)
  • Ho W-H, Lee K-T, Chen H-Y, Ho T-W, Chiu H-C (2012) Disease-Free Survival after Hepatic Resection in Hepatocellular Carcinoma Patients: A Prediction Approach Using Artificial Neural Network. (plos.org)
  • Computing
  • Bio-Inspired Computing through Artificial Neural Network. (igi-global.com)
  • Multi-core platforms significantly promote SDRs' parallel computing capacities, enabling them to adopt artificial intelligent techniques, i.e., deep learning, to manage routing paths. (ieee.org)
  • This problem is fixed by Edge Cloud Computing, where the users offload tasks they cannot run to cloudlet servers in the edge of the network. (ieee.org)
  • dynamics
  • yet, the relation between neural dynamics and symbolic representations and operations is still unclear in traditional eliminative connectionism. (researchgate.net)
  • perspectives
  • From different perspectives, neural computation provides an alternative methodology to understand brain functions and cognitive process and to solve challenging real-world problems effectively. (springer.com)
  • automata
  • Finally, we present a mapping between nonlinear dynamical automata and recurrent artificial neural networks. (researchgate.net)
  • The resulting networks simulate automata in real-time and are programmed directly, in absence of network training. (researchgate.net)
  • To discuss the unique characteristics of the architecture and their consequences, we present two examples: i) the design of a Central Pattern Generator from a finite-state locomotive controller, and ii) the creation of a network simulating a system of interactive automata that supports the parsing of garden-path sentences as investigated in psycholinguistics experiments. (researchgate.net)
  • optimization
  • In the book, students discover that bacteria communicate, that DNA can be used for performing computations, how evolution solves optimization problems, that the way ants organize their nests can be applied to solve clustering problems, and what the human immune system can teach us about protecting computer networks. (garlandscience.com)
  • models
  • Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire models, which facilitates comparison with existing neural network and observation models. (researchgate.net)
  • This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. (frontiersin.org)
  • derive
  • Starting from a reduced threecompartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential that contributes to the local field potential of a neural population. (researchgate.net)
  • model
  • The results show that the proposed method can accurately determine the model coefficients provided that the network is properly trained. (hindawi.com)
  • machine
  • A. Chandola and Mahalanobis described the use of corpus pattern for alignment and reordering of words for English to Hindi machine translation using the neural network [ 10 ], but still there are a lot of possibilities to develop a MT System for Hindi to increase the accuracy of MT. Some of the important works on Hindi are discussed in Section 2 . (hindawi.com)
  • control
  • The mapping defines an architecture characterized by its granular modularity, where data, symbolic operations and their control are not only distinguishable in activation space, but also spatially localizable in the network itself, while maintaining a distributed encoding of symbolic representations. (researchgate.net)
  • time
  • The book by Lamm and Unger methodically covers exciting developments in biological computation, offering for the first time a broad perspective of this important cutting-edge field of research. (garlandscience.com)
  • book
  • Researchers, graduate students and industrial practitioners in the broad areas of neural computation would benefit from the state-of-the-art work collected in this book. (springer.com)