###### evolutionary

- Proceedings of CEC 2004 (Congress on Evolutionary Computation). (iastate.edu)
- An improved taxonomy of evolutionary computation problems. (iastate.edu)
- These intelligent models include the intelligent techniques such as Artificial Neural Network (ANN), evolutionary computation, swarm intelligence, fuzzy system, artificial immune system accompanied by fuzzy logic, expert system, deductive reasoning. (igi-global.com)
- These algorithms are broadly categorized as evolutionary computation and swarm intelligence (SI) algorithms. (igi-global.com)
- Evolutionary computation is a term used to describe algorithms which were inspired by 'survival of the fittest' or 'natural selection' principles (McCulloch et al. (igi-global.com)
- Evolutionary- and Quantum-Inspired Computation. (springer.com)
- These new analytical tools, known collectively as computational intelligence tools, include artificial neural networks, fuzzy systems, and evolutionary computation. (semanticscholar.org)
- Evolutionary Computation relies heavily on the use of neo-Darwinian views. (drexel.edu)
- Evolutionary computation covers a wide continuum of areas. (drexel.edu)
- Evolutionary Computation is often applied to very complex problems in scientific fields. (drexel.edu)
- Evolutionary computation is used in physically simulated animation through space time constraints. (drexel.edu)
- Evolutionary Computation has two approaches to control, an on-line approach and an off-line approach. (drexel.edu)
- Evolutionary computation allows for a controller that is able to adapt to a system that is able to change over time. (drexel.edu)
- Frontiers of Evolutionary Computation brings together eleven contributions by international leading researchers discussing what significant issues still remain unresolved in the field of Evolutionary Computation (EC). (booktopia.com.au)
- Frontiers of Evolutionary Computation is ideal for researchers and students who want to follow the process of EC problem-solving and for those who want to consider what frontiers still await their exploration. (booktopia.com.au)
- This is a diverse collection of eleven papers that share the common theme of posing open problems and pointing out possible directions of future research, all written by leading researchers in the field of evolutionary computation (EC). (booktopia.com.au)

###### ANNs

- Artificial Neural Networks (ANNs) are bio-inspired models of neural computation that have proven highly effective. (rug.nl)
- Still, ANNs lack a natural notion of time, and neural units in ANNs exchange analog values in a frame-based manner, a computationally and energetically inefficient form of communication. (rug.nl)
- While artificial Spiking Neural Networks (SNNs) can be constructed by replacing the units of an ANN with spiking neurons, the performance of current SNNs does not match from that of deep ANNs on hard benchmarks and these SNNs use much higher firing rates compared to their biological counterparts, limiting their efficiency. (rug.nl)
- Here we show how spiking neurons that employ an efficient form of neural coding can be used to construct SNNs that match high-performance ANNs and exceed state-of-the-art in SNNs on important benchmarks, while requiring much lower average firing rates. (rug.nl)
- Neural units in ANNs trained with this transfer function can be substituted directly with adaptive spiking neurons, and the resulting Adaptive SNNs (AdSNNs) can carry out classification in deep neural networks using up to an order of magnitude fewer spikes compared to previous AdSNNs. (rug.nl)
- Session I discussed background theory for machine learning, graph computation, artificial neural networks (ANNs) and the basics of deep learning. (mcgill.ca)
- Perceptron-type ANNs and an introduction to convolutional networks were also covered in the first session. (mcgill.ca)
- Biologically Inspired Artificial Neural Networks, such as Spiking Neural Networks (SNNs), promise to provide significant advances over classic Artificial Neural Networks (ANNs) by performing computations in ways similar to the living brain. (brain2grid.com)
- It bridges the gap between oversimplified ANNs and living neural networks. (brain2grid.com)
- Recently, machine-learning and statistical methods have been applied to develop prediction models for clinical diagnosis and treatment, e.g., artificial neural networks (ANNs), logistic regression (LR) and decision tree (DT) (see, e.g., - and the references therein). (plos.org)
- Artificial neural networks (henceforth ANNs) are a particularly promising branch on the tree of soft computing, as they possess the ability to determine non-linear relationships, and are particularly adept at dealing with noisy datasets. (igi-global.com)

###### convolutional neural networks

- Head pose estimation in the wild using convolutional neural networks and adaptive gradient methods. (plymouth.ac.uk)
- Convolutional Neural Networks (CNNs) have shown a great deal of success in diverse application domains including computer vision, speech recognition, and natural language processing. (ieee.org)

###### computational

- The area of biologically inspired computing, or biological computation , involves the development of new, biologically based techniques for solving difficult computational problems. (garlandscience.com)
- The conduction delays between neurons are one set of parameters that can be tuned to improve network performance on computational tasks, however no biologically inspired delay learning rules have been adopted by the artificial neural network community. (brain2grid.com)
- This work shows the computational properties of delay update rules that are based on how delay change in living neural networks, as well as how the actual biological data can be used to improve performance for a prediction task. (brain2grid.com)
- Computational biology, especially building phylogenetic trees and networks. (iastate.edu)
- Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. (springer.com)
- The ICANN conference is organized annually by the European Neural Network Society in cooperation with the International Neural Network Society, the Japanese Neural Network Society and the IEEE Computational Intelligence Society. (springer.com)
- The edited book aims to reflect the latest progresses made in different areas of neural computation, including theoretical neural computation, biologically plausible neural modeling, computational cognitive science, artificial neural networks - architectures and learning algorithms and their applications in real-world problems. (springer.com)

###### architectures

- However, as the size of datasets and the depth of neural network architectures continue to grow, it is imperative to design high-performance and energy-efficient computing hardware for training CNNs. (ieee.org)

###### IWANN

- The papers presented in this volume are carefully reviewed versions of the talks delivered at the International Workshop on Artificial Neural Networks (IWANN '93) organized by the Universities of Catalonia and the Spanish Open University at Madrid and held at Barcelona, Spain, in June 1993. (springer.com)
- With the download Biological and Artificial Computation: From Neuroscience to Technology: International Work Conference on Artificial and Natural Neural Networks, IWANN\'97 Lanzarote, Canary Islands, Spain, June 4-6, of the recept on Instagram, acheter is an site to admit web. (krautstein.info)
- Any organs or download Biological and Artificial Computation: From Neuroscience to Technology: International Work Conference on Artificial and Natural Neural Networks, IWANN\'97 Lanzarote, Canary Islands, would have just aided. (krautstein.info)
- Verleysen M., Francois D. (2005), The curse of dimensionality in data mining and time series prediction, 8th International Workshop on Artificial Neural Networks, IWANN. (edu.pl)

###### algorithms

- In this new method, we utilize artificial neural networks to initiate the genetic algorithm, so that the high computation cost of genetic algorithms for synthesizing holograms is significantly reduced, while the high diffraction efficiency and uniformity are still ensured. (spiedigitallibrary.org)
- Soft computing is normally accepted to include the three key areas of fuzzy logic, artificial neural networks, and probabilistic reasoning (which include genetic algorithms, chaos theory, etc. (igi-global.com)

###### Intelligence

- Artificial Intelligence (incl. (springer.com)
- Artificial intelligence techniques within this realm attempt to solve problems by applying physical laws and processes. (igi-global.com)

###### 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)

###### Proceedings

- Conference proceedings for ANNIE 2004 (Artificial Neural Networks in Engineering). (iastate.edu)

###### classification

- Artificial neural networks have proven particularly effective for nonlinear mapping based on human knowledge and are attracting interest for use in solving complex classification problems , . (plos.org)

###### 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)

###### neuronal

- According to standard teachings, dendrites are passive cables that shuttle electrical signals to the neuronal body, where all the computation occurs. (singularityhub.com)
- Evolution of neuronal computation. (tau.ac.il)

###### quantum neural

- The quantum neural based pattern recognizer is used to recognize and learn the pattern of corpus, using the information of part of speech of individual word in the corpus, like a human. (hindawi.com)
- This paper presents the quantum neural based machine translation for Hindi to English. (hindawi.com)
- The quantum neural network (QNN) based approach increases the accuracy during the knowledge adoptability. (hindawi.com)
- The machine translation is done using the new approach based on quantum neural network which learns the patterns of language using the pair of sentences of Hindi and English. (hindawi.com)

###### neurons

- We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. (researchgate.net)
- Recently, a team from UCLA discovered a hidden layer of neural communication buried within the long, tortuous projections of neurons-the dendrites. (singularityhub.com)

###### 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)

###### patterns

- Like linguists deciphering an alien communication, scientists carefully dissect the patterns of neural firing to try to distill the grammatical rules of the brain-the "neural code. (singularityhub.com)

###### 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)

###### cortical

- Evolution of cortical computation - investigation of the amphibian dorsal pallium. (tau.ac.il)

###### Spiking

- Spiking Neural Networks use the precise timing of action potentials to convey meaning. (brain2grid.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)

###### Systems

- Ways in which these computations might be realized in real neural systems are also considered. (frontiersin.org)
- Financial Trading Systems Using Artificial Neural Networks. (igi-global.com)

###### 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)

###### prediction

- The three prediction models included an artificial neural network (ANN) model, a logistic regression (LR) model, and a decision tree (DT) model. (plos.org)

###### 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)

###### International Conference

- Trend in Neural Computation includes twenty chapters either contributed from leading experts or formed by extending well selected papers presented in the 2005 International Conference on Natural Computation. (springer.com)

###### applications

- AdSNNs thus hold promise as a novel and efficient model for neural computation that naturally fits to temporally continuous and asynchronous applications. (rug.nl)
- In recent times, the introduction of complex-valued neural networks (CVNNs) has widened the scope and applications of artificial neural network (ANN) [ 25 - 34 ]. (hindawi.com)

###### 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)

###### biology

- A unified overview of computer science ideas inspired by biology, Biological Computation presents the most fundamental and significant concepts in this area. (garlandscience.com)
- I read this book in one breath-it opens vistas on how the fields of computation and biology can inspire each other. (garlandscience.com)

###### analysis

- Schnitzer D., Flexer A., Tomasev N. (2014), Choosing the metric in highdimensional spaces based on hub analysis, European Symposium on Artificial Neural Networks ESANN. (edu.pl)

###### computer science

- This is a wonderful treatise on bio-inspired computation, written from a computer science perspective. (garlandscience.com)

###### accurately

- QNN learns and predicts more accurately and needs less computation power and time for learning in comparison to artificial neural network. (hindawi.com)

###### Learning

- This has given rise to the development of Artificial Neural Networks where computation is distributed over a great number of local processing elements with a high degree of connectivityand in which external programming is replaced with supervised and unsupervised learning. (springer.com)
- White H. (1989), Learning in artificial neural networks: a statistical perspective, „Neural Computation", Vol. 1. (edu.pl)

###### 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)

###### areas

- It is the premier European event covering all topics concerned with neural networks and related areas. (springer.com)