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The book presents a coherent understanding of computational
intelligence from the perspective of what is known as "intelligent
computing" with high-dimensional parameters. It critically
discusses the central issue of high-dimensional neurocomputing,
such as quantitative representation of signals, extending the
dimensionality of neuron, supervised and unsupervised learning and
design of higher order neurons. The strong point of the book is its
clarity and ability of the underlying theory to unify our
understanding of high-dimensional computing where conventional
methods fail. The plenty of application oriented problems are
presented for evaluating, monitoring and maintaining the stability
of adaptive learning machine. Author has taken care to cover the
breadth and depth of the subject, both in the qualitative as well
as quantitative way. The book is intended to enlighten the
scientific community, ranging from advanced undergraduates to
engineers, scientists and seasoned researchers in computational
intelligence.
This book presents state-of-the-art blockchain and AI advances in
health care. Healthcare service is increasingly creating the scope
for blockchain and AI applications to enter the biomedical and
healthcare world. Today, blockchain, AI, ML, and deep learning are
affecting every domain. Through its cutting-edge applications, AI
and ML are helping transform the healthcare industry for the
better. Blockchain is a decentralization communication platform
that has the potential to decentralize the way we store data and
manage information. Blockchain technology has potential to reduce
the role of middleman, one of the most important regulatory actors
in our society. Transactions are simultaneously secure and
trustworthy due to the use of cryptographic principles. In recent
years, blockchain technology has become very trendy and has
penetrated different domains, mostly due to the popularity of
cryptocurrencies. One field where blockchain technology has
tremendous potential is health care, due to the need for a more
patient-centric approach in healthcare systems to connect disparate
systems and to increase the accuracy of electronic healthcare
records (EHRs).
Computer simulation of fluid flows requires numerical solution of
Partial Differential Equations (PDEs) which involves discretization
methods such as Finite Volume Method (FVM). These methods produce a
large system of linear equations which are difficult to solve.
Iterative (Krylov Subspace) solvers are one of the best ways to
deal with such large systems. These systems need huge amount of
memory as well as they are computationally expensive. Modern
supercomputers facilitate to run the simulations on multiprocessors
by writing efficient parallel algorithms for iterative solvers.
This book provides good background of Krylov Subspace solvers and
computational methods for multiphase fluid flows. Furthermore,
detailed discussions on developing parallel algorithms for these
solvers have been provided using the special data structures
facilitating inter-processor communications. It is a very useful
book for advanced undergraduate and graduate students, who want to
gain knowledge about parallel numerical algorithms applicable to
Computation Fluid Dynamics (CFD) problems.
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Wethair
Phil Scott
Hardcover
R862
Discovery Miles 8 620
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