Learn IT - Books tags stochastic

Optimality and Risk - Modern Trends in Mathematical Finance: The Kabanov Festschrift

Springer, 2009

Problems of stochastic optimization and various mathematical aspects of risk are the main themes of this contributed volume. The readers learn about the recent results and techniques of optimal investment, risk measures and derivative pricing. There are also papers touching upon credit risk, martingale theory and limit theorems.

...

Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing

Artech House Publishers, 2005

This authoritative volume on statistical and adaptive signal processing offers you a unified, comprehensive and practical treatment of spectral estimation, signal modeling, adaptive filtering, and array processing. Packed with over 3,000 equations and more than 300 illustrations, this unique resource provides you with balanced coverage of...

Singular Perturbation Theory: Mathematical and Analytical Techniques with Applications to Engineering

Springer, 2004

The importance of mathematics in the study of problems arising from the real world, and the increasing success with which it has been used to model situations ranging from the purely deterministic to the stochastic, is well established. The purpose of the set of volumes to which the present one belongs is to make available authoritative, up to...

Nonlinear Stochastic Operator Equations

Academic Press, 1986

A previous volume, Stochastic Systems (1983), was the first systematic book bringing nonlinear and stochastic equations within the reach of engi neers and physicists concerned with the difficulties of real systems and fron tier problems in which conventional techniques such as linearization and perturbation are not sufficient...

Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks

CreateSpace Independent Publishing Platform, 2015

Neural networks have been a mainstay of artificial intelligence since its earliest days. Now, exciting new technologies such as deep learning and convolution are taking neural networks in bold new directions. In this book, we will demonstrate the neural networks in a variety of real-world tasks such as image recognition and data science. We...

Mathematical Methods and Algorithms for Signal Processing

Pearson Education, 1999

Mathematical Methods and Algorithms for Signal Processing tackles the challenge of providing readers and practitioners with the broad tools of mathematics employed in modern signal processing. Building from an assumed background in signals and stochastic processes, the book provides a solid foundation in analysis, linear...

Signal Analysis: Wavelets, Filter Banks, Time-Frequency Transforms and Applications

John Wiley & Sons, 1999

"...excellent and interesting reading for digital signal processing engineers and designers and for postgraduate students in electrical and computer faculties." (Mathematical Reviews, 2002d)

Signal Analysis explores methods that offer an insight into the properties of signals and stochastic processes. This...

Nonlinear Differential Equations in Physics: Novel Methods for Finding Solutions

Springer, 2019

This book discusses various novel analytical and numerical methods for solving partial and fractional differential equations. Moreover, it presents selected numerical methods for solving stochastic point kinetic equations in nuclear reactor dynamics by using Euler–Maruyama and strong-order Taylor numerical methods. The book...

Spoken Language Processing

John Wiley & Sons, 2009

Speech processing addresses various scientific and technological areas. It includes speech analysis and variable rate coding, in order to store or transmit speech. It also covers speech synthesis, especially from text, speech recognition, including speaker and language identification, and spoken language understanding.

This book...

Flowgraph Models for Multistate Time-to-Event Data (Wiley Series in Probability and Statistics)

John Wiley & Sons, 2004

The main purpose of this book is to present an introduction to flowgraph models for time-to-event data. The focus is on stochastic models for censored time-to-event data with competing risks and recurrent events. The applications are geared to survivalanalysis and reliability. I view flowgraph models as providing a methodology for data...

MATLAB® Recipes for Earth Sciences

Springer, 2007

MATLAB^® is used in a wide range of applications in geosciences, such as image processing in remote sensing, generation and processing of digital elevation models and the analysis of time series. This book introduces methods of data analysis in geosciences using MATLAB such as basic statistics for univariate, bivariate and...

Stochastic Approximation and Its Application (Nonconvex Optimization and Its Applications)

Springer, 2002

This book presents the recent development of stochastic approximation algorithms with expanding truncations based on the TS (trajectory-subsequence) method, a newly developed method for convergence analysis. This approach is so powerful that conditions used for guaranteeing convergence have been considerably weakened in comparison with those...

Result Page: 14 13 12 11 10 9 8 7 6 5 4 3 2 1