Neil Gordon – författare

Monte Carlo methods are revolutionising the on-line analysis of data in fields as diverse as financial modelling, target tracking and computer vision. These methods, appearing under the names of bootstrap filters, condensation, optimal Monte Carlo filters, particle filters and survial of the fittest, have made it possible to solve numerically many complex, non-standarard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques, including convergence results and applications to tracking, guidance, automated target recognition, aircraft navigation, robot navigation, econometrics, financial modelling, neural networks,optimal control, optimal filtering, communications, reinforcement learning, signal enhancement, model averaging and selection, computer vision, semiconductor design, population biology, dynamic Bayesian networks, and time series analysis. This will be of great value to students, researchers and practicioners, who have some basic knowledge of probability. Arnaud Doucet received the Ph. D. degree from the University of Paris- XI Orsay in 1997. From 1998 to 2000, he conducted research at the Signal Processing Group of Cambridge University, UK. He is currently an assistant professor at the Department of Electrical Engineering of Melbourne University, Australia. His research interests include Bayesian statistics, dynamic models and Monte Carlo methods. Nando de Freitas obtained a Ph.D. degree in information engineering from Cambridge University in 1999. He is presently a research associate with the artificial intelligence group of the University of California at Berkeley. His main research interests are in Bayesian statistics and the application of on-line and batch Monte Carlo methods to machine learning.

Working Positively with Personality Disorder in Secure Settings provides a positive, compassionate and evidence-based guide to working with patients with personality disorders. Unique in both its coverage and in its positive and evidence-based approach to working with patients with personality disordersWritten with a practical focus by experienced practitioners in the fieldOffers a broad approach, with contributions from forensic and clinical psychologists, nurses, and therapistsCovers therapy and therapeutic relationships, and issues of supervision, workforce development, treatment evaluation, team dynamics and managing boundariesIncludes a strong patient focus and a number of personal accounts from patients who have received therapy themselves

Working Positively with Personality Disorder in Secure Settings provides a positive, compassionate and evidence-based guide to working with patients with personality disorders. Unique in both its coverage and in its positive and evidence-based approach to working with patients with personality disordersWritten with a practical focus by experienced practitioners in the fieldOffers a broad approach, with contributions from forensic and clinical psychologists, nurses, and therapistsCovers therapy and therapeutic relationships, and issues of supervision, workforce development, treatment evaluation, team dynamics and managing boundariesIncludes a strong patient focus and a number of personal accounts from patients who have received therapy themselves

Monte Carlo methods are revolutionising the on-line analysis of data in fields as diverse as financial modelling, target tracking and computer vision. These methods, appearing under the names of bootstrap filters, condensation, optimal Monte Carlo filters, particle filters and survial of the fittest, have made it possible to solve numerically many complex, non-standarard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques, including convergence results and applications to tracking, guidance, automated target recognition, aircraft navigation, robot navigation, econometrics, financial modelling, neural networks,optimal control, optimal filtering, communications, reinforcement learning, signal enhancement, model averaging and selection, computer vision, semiconductor design, population biology, dynamic Bayesian networks, and time series analysis. This will be of great value to students, researchers and practicioners, who have some basic knowledge of probability. Arnaud Doucet received the Ph. D. degree from the University of Paris- XI Orsay in 1997. From 1998 to 2000, he conducted research at the Signal Processing Group of Cambridge University, UK. He is currently an assistant professor at the Department of Electrical Engineering of Melbourne University, Australia. His research interests include Bayesian statistics, dynamic models and Monte Carlo methods. Nando de Freitas obtained a Ph.D. degree in information engineering from Cambridge University in 1999. He is presently a research associate with the artificial intelligence group of the University of California at Berkeley. His main research interests are in Bayesian statistics and the application of on-line and batch Monte Carlo methods to machine learning.

When journalist Benjamin Schulberg discovers a link between liberal lawyer Jim Grant and a notorious Vietnam-era fugitive, the world that Jim has carefully built for himself and his daughter collapses.His cover blown, Jim is forced to go on the run after decades living under his false identity. Still wanted for his part in an act of domestic terrorism in 1974, he must travel deep into his past to clear his name and save his young daughter.Set against the backdrop of the Vietnam war, The Company You Keep is an intelligent thriller about political ideals, family loyalties, and the shadowy world of the radical anti-war group the Weather Underground.

2011. Isabel Montgomery, investigative journalist, is the granddaughter of one of America's most radical lawyers, the daughter of one of America's most famous protesters. She's going to expose the Obama administration's unconstitutional surveillance of its citizens in the New York Times.Forced into hiding after her story breaks, she takes refuge in her grandparents' abandoned home. There, surrounded by the past she's run from for years, she makes a discovery that sees her question everything that led her to this moment.You're A Big Girl Now is a gripping, intelligent thriller about the moral and political responsibilities of the citizen in the modern world. For every choice, there is a consequence. The question is: should Isabel suffer for a choice she didn't make?

With this hands-on guide, you can develop more accurate and reliable nonlinear filter designs and more precisely predict the performance of these designs. You can also apply particle filters to tracking a ballistic object, detection and tracking of stealthy targets, tracking through the blind Doppler zone, bi-static radar tracking, passive ranging (bearings-only tracking) of manoeuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.

In an era where technology shapes every aspect of our lives, the need for ethical guidance in IT has never been more important. Getting Started with Tech Ethics is your essential resource for understanding and applying ethics in the fast-evolving tech environment.This book equips IT professionals, from beginners to experienced leaders, with a clear ethical framework to operate within ethical boundaries, providing practical insights and real-world examples, including high-profile cases like the Horizon software scandal. Whether you’re a student beginning your journey in computing, an early-career developer navigating real-world complexities for the first time, or a seasoned professional seeking to refresh your ethical lens, this book is written with you in mind.This book brings together the insights of leading figures from across the technology landscape—academics, consultants, and industry veterans. Elevate your professionalism, protect your organization, and contribute to a more responsible tech future with this indispensable guide to IT ethics.

This book demonstrates how nonlinear/non-Gaussian Bayesian time series estimation methods were used to produce a probability distribution of potential MH370 flight paths.