0
Your cart

Your cart is empty

Browse All Departments
  • All Departments
Price
  • R1,000 - R2,500 (1)
  • R2,500 - R5,000 (2)
  • -
Status
Brand

Showing 1 - 3 of 3 matches in All Departments

The Relevance of the Time Domain to Neural Network Models (Hardcover, 2012): A.Ravishankar Rao, Guillermo A. Cecchi The Relevance of the Time Domain to Neural Network Models (Hardcover, 2012)
A.Ravishankar Rao, Guillermo A. Cecchi
R4,363 Discovery Miles 43 630 Ships in 10 - 15 working days

A significant amount of effort in neural modeling is directed towards understanding the representation of information in various parts of the brain, such as cortical maps [6], and the paths along which sensory information is processed. Though the time domain is integral an integral aspect of the functioning of biological systems, it has proven very challenging to incorporate the time domain effectively in neural network models. A promising path that is being explored is to study the importance of synchronization in biological systems. Synchronization plays a critical role in the interactions between neurons in the brain, giving rise to perceptual phenomena, and explaining multiple effects such as visual contour integration, and the separation of superposed inputs. The purpose of this book is to provide a unified view of how the time domain can be effectively employed in neural network models. A first direction to consider is to deploy oscillators that model temporal firing patterns of a neuron or a group of neurons. There is a growing body of research on the use of oscillatory neural networks, and their ability to synchronize under the right conditions. Such networks of synchronizing elements have been shown to be effective in image processing and segmentation tasks, and also in solving the binding problem, which is of great significance in the field of neuroscience. The oscillatory neural models can be employed at multiple scales of abstraction, ranging from individual neurons, to groups of neurons using Wilson-Cowan modeling techniques and eventually to the behavior of entire brain regions as revealed in oscillations observed in EEG recordings. A second interesting direction to consider is to understand the effect of different neural network topologies on their ability to create the desired synchronization. A third direction of interest is the extraction of temporal signaling patterns from brain imaging data such as EEG and fMRI. Hence this Special Session is of emerging interest in the brain sciences, as imaging techniques are able to resolve sufficient temporal detail to provide an insight into how the time domain is deployed in cognitive function. The following broad topics will be covered in the book: Synchronization, phase-locking behavior, image processing, image segmentation, temporal pattern analysis, EEG analysis, fMRI analyis, network topology and synchronizability, cortical interactions involving synchronization, and oscillatory neural networks. This book will benefit readers interested in the topics of computational neuroscience, applying neural network models to understand brain function, extracting temporal information from brain imaging data, and emerging techniques for image segmentation using oscillatory networks

The Relevance of the Time Domain to Neural Network Models (Paperback): A.Ravishankar Rao, Guillermo A. Cecchi The Relevance of the Time Domain to Neural Network Models (Paperback)
A.Ravishankar Rao, Guillermo A. Cecchi
R4,333 Discovery Miles 43 330 Ships in 10 - 15 working days

A significant amount of effort in neural modeling is directed towards understanding the representation of information in various parts of the brain, such as cortical maps 6], and the paths along which sensory information is processed. Though the time domain is integral an integral aspect of the functioning of biological systems, it has proven very challenging to incorporate the time domain effectively in neural network models. A promising path that is being explored is to study the importance of synchronization in biological systems. Synchronization plays a critical role in the interactions between neurons in the brain, giving rise to perceptual phenomena, and explaining multiple effects such as visual contour integration, and the separation of superposed inputs.

The purpose of this book is to provide a unified view of how the time domain can be effectively employed in neural network models. A first direction to consider is to deploy oscillators that model temporal firing patterns of a neuron or a group of neurons. There is a growing body of research on the use of oscillatory neural networks, and their ability to synchronize under the right conditions. Such networks of synchronizing elements have been shown to be effective in image processing and segmentation tasks, and also in solving the binding problem, which is of great significance in the field of neuroscience. The oscillatory neural models can be employed at multiple scales of abstraction, ranging from individual neurons, to groups of neurons using Wilson-Cowan modeling techniques and eventually to the behavior of entire brain regions as revealed in oscillations observed in EEG recordings. A second interesting direction to consider is to understand the effect of different neural network topologies on their ability to create the desired synchronization. A third direction of interest is the extraction of temporal signaling patterns from brain imaging data such as EEG and fMRI. Hence this Special Session is of emerging interest in the brain sciences, as imaging techniques are able to resolve sufficient temporal detail to provide an insight into how the time domain is deployed in cognitive function.

The following broad topics will be covered in the book: Synchronization, phase-locking behavior, image processing, image segmentation, temporal pattern analysis, EEG analysis, fMRI analyis, network topology and synchronizability, cortical interactions involving synchronization, and oscillatory neural networks.

This book will benefit readers interested in the topics of computational neuroscience, applying neural network models to understand brain function, extracting temporal information from brain imaging data, and emerging techniques for image segmentation using oscillatory networks

A Taxonomy for Texture Description and Identification (Paperback, Softcover reprint of the original 1st ed. 1990):... A Taxonomy for Texture Description and Identification (Paperback, Softcover reprint of the original 1st ed. 1990)
A.Ravishankar Rao
R1,500 Discovery Miles 15 000 Ships in 10 - 15 working days

A central issue in computer vision is the problem of signal to symbol transformation. In the case of texture, which is an important visual cue, this problem has hitherto received very little attention. This book presents a solution to the signal to symbol transformation problem for texture. The symbolic de- scription scheme consists of a novel taxonomy for textures, and is based on appropriate mathematical models for different kinds of texture. The taxonomy classifies textures into the broad classes of disordered, strongly ordered, weakly ordered and compositional. Disordered textures are described by statistical mea- sures, strongly ordered textures by the placement of primitives, and weakly ordered textures by an orientation field. Compositional textures are created from these three classes of texture by using certain rules of composition. The unifying theme of this book is to provide standardized symbolic descriptions that serve as a descriptive vocabulary for textures. The algorithms developed in the book have been applied to a wide variety of textured images arising in semiconductor wafer inspection, flow visualization and lumber processing. The taxonomy for texture can serve as a scheme for the identification and description of surface flaws and defects occurring in a wide range of practical applications.

Free Delivery
Pinterest Twitter Facebook Google+
You may like...
Abnormal Child Psychology
Eric J. Mash, David Wolfe Hardcover R1,332 R1,243 Discovery Miles 12 430
Resurrection
Danielle Steel Paperback R385 R349 Discovery Miles 3 490
The Passenger
Cormac McCarthy Paperback R385 R349 Discovery Miles 3 490
Broken Country
Clare Leslie Hall Paperback R395 R353 Discovery Miles 3 530
Zeus Van Wyngaardt En Die Skrikgodin
Julio Agrella Paperback R333 Discovery Miles 3 330
Deconstruction without Derrida
Martin McQuillan Hardcover R4,922 Discovery Miles 49 220
Blood's Inner Rhyme - An…
Antjie Krog Paperback R360 R299 Discovery Miles 2 990
The Origins of Deconstruction
M. McQuillan, I. Willis Hardcover R1,532 Discovery Miles 15 320
Buried In The Chest
Lindani Mbunyuza-Memani Paperback R260 R240 Discovery Miles 2 400
Rocklands - On Becoming The First…
Liezille Jean Jacobs Paperback R300 R277 Discovery Miles 2 770

 

Partners