Book Description:
An artificial neural network (ANN) is a type of artificial intelligence technology which implements more complex data-analysis features into existing applications by an intelligent, human-like application of knowledge. ANN can be considered as a mathematical or computational model based on biological (brain) neural networks. ANN is an adaptive system that changes its structure based on external or internal information that is processed within the network during the learning stage. ANNs implement algorithms that attempt to achieve neurologically-related processes and performances such as learning from experience, making generalizations from similar situations and judging states where poor results were achieved in the past. This new and important book gathers the most current research from across the globe in the study of artificial neural networks.
(Imprint: Nova)

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Table of Contents:
Preface

Artificial Neural Network Modeling of Water and Wastewater Treatment Processes;pp. 1-60
(Ali R. Khataee, Masoud B. Kasiri, Department of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz, Iran, and others)

Recent Advances and Challenges in the Application of Artificial Neural Networks (ANN) in Neurological Sciences: An Overview;pp. 61-99
(Penka A. Atanassova, Borislav D. Dimitrov, Department of Neurology, Medical University, Plovdiv, Bulgaria, and others)

Different Types of Applications Performed with Different Types of Neural Networks;pp. 101-135
(Silvia Curteanu, Gheorghe Asachi Technical University, Department of Chemical Engineering, Iasi, Romania)

Application of Artificial Neural Networks in Wire Electro-Discharge Machining (WEDM);pp. 137-184
(Eva Portillo, Automatic Control and Systems Engineering Department, University of the Basque Country, Bilbao, Spain)

Artificial Neural Network Training and Software Implementation Techniques;pp. 185-218
(Ali Kattan, Rosni Abdullah, Zong Woo Geem, School of Computer Science, Universiti Sains Malaysia, Penang, Malaysia, and others)

Artificial Neural Networks in Small-Signal and Noise Modeling of Microwave Transistors;pp. 219-263
(Zlatica Marinković, Vera Marković, Alina Caddemi, Faculty of Electronic Engineering, University of Niš, Niš, Serbia, and others)

Parameter Extraction of Advanced Semiconductor Detectors with Artificial Neural Network;pp. 265-300
(Shahyar Saramad, Vahid Esmaeili Sani, Gholamreza Ansarifar, Faculty of Physics, Amirkabir University of Technology, Tehran, Iran, and others)

Processing of Impedance Data Records using Artificial Neural Networks;pp. 301-330
(Xavier Muñoz-Berbel, Manel del Valle, Montserrat Cortina-Puig, Departamento de Fisiología Médica y Biofísica, Facultad de Medicina, Universidad de Sevilla, Sevilla, Spain, and others)

Identification of Patients Based on Spectral Analysis of Heart Rate Variability using Artificial Neural Networks;pp. 331-360
(Abdulnasir Hossen, Nazar Elfadil, Department of Electrical & Computer Engineering, College of Engineering, Sultan Qaboos University, Al-Khoud, Muscat, Sultanate of Oman, and others)

Modelling the Ultrafiltration of Protein Solutions by Artificial Neural Networks;pp. 361-384;pp. 361-384
(Rubén Ibáñez, M. Carmen Almécija, Antonio Guadix, Emilia M. Guadix, Department of Chemical Engineering, University of Granada, Spain)

Artificial Neural Networks in the Optimization of Microemulsion Liquid
Chromatography Retention and Resolution;pp. 385-409
(Biljana Jančić–Stojanović, Anđelija Malenović, Darko Ivanović, Mirjana Medenica, Faculty of Pharmacy, Department of Drug Analysis, Vojvode Stepe, Belgrade, Serbia, and others)

Index pp.411-426