This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests. The models are simple to understand and interpret and provide a useful tool to describe the global dynamics of the landmark configurations. However, because of the non-Euclidean nature of shape spaces, distributions in shape spaces are not straightforward to obtain.The book explores the use of th...

Statistical shape analysis is a geometrical analysis from a set of shapes in which statistics are measured to describe geometrical properties from similar shapes or different groups, for instance, the difference between male and female Gorilla skull shapes, normal and pathological bone shapes, etc. Some of the important aspects of shape analysis are to obtain a measure of distance between shapes, to estimate average shapes from a (possibly random) sample and to estimate shape variability i...

Perceptual organization is the neuro-cognitive process that enables us to perceive scenes as structured wholes consisting of objects arranged in space. Simplicity in Vision explores the intriguing idea that these perceived wholes are given by the simplest organizations of the scenes. Peter A. van der Helm presents a truly multidisciplinary approach to answer fundamental questions such as: Are simplest organizations sufficiently reliable to guide our actions? What is the nature of the regul...

This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed and latent variables.Basic and Advanced Bayesian Structural Equation Model**ing introduces basic and advanced SEMs for analyzing various kinds of complex data, such as ordered and unordered categorical data, multilevel data, mixture data, longitudinal data, highly non-normal data, as well as some of t...

This comprehensive and authoritative text/reference presents a unique, multidisciplinary perspective on Shape Perception in Human and Computer Vision. Rather than focusing purely on the state of the art, the book provides viewpoints from world-class researchers reflecting broadly on the issues that have shaped the field. Drawing upon many years of experience, each contributor discusses the trends followed and the progress made, in addition to identifying the major challenges that ...

This book describes a novel methodology for studying algorithmic skills, intended as cognitive activities related to rule-based symbolic transformation, and argues that some human computational abilities may be interpreted and analyzed as genuine examples of extended cognition. It shows that the performance of these abilities relies not only on innate neurocognitive systems or language-related skills, but also on external tools and general agent–environment interactions. Further, it assert...

The field's leading text, now completely updated.Modeling dynamical systems — theory, methodology, and applications.Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-f...

First published in 1983. Psychological data are segments of life histories; as such they are ordered sequences of observations and by definition time series. Yet they are often anything but well behaved; what regularities and invariances they have are buried from all but the most persistent investigator. The most common methods of representing quantitative results in psychology are frozen outside time; thus they deliberately average out much of the sequential structure that holds any spars...

Our understanding of how the human brain performs mathematical calculations is far from complete, but in recent years there have been many exciting breakthroughs by scientists all over the world. Now, in The Number Sense, Stanislas Dehaene offers a fascinating look at this recent research, in an enlightening exploration of the mathematical mind. Dehaene begins with the eye-opening discovery that animals--including rats, pigeons, raccoons, and chimpanzees--can perform simple mathem...

Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques.This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJM...

This book provides a historic overview of what is defined as "soft computing" with its techniques: neural networks, fuzzy logic, genetic algorithms and cellular automata.

Big ideas in the mathematics curriculum for older school students, especially those that are hard to learn and hard to teach, are covered in this book. It will be a first port of call for research about teaching big ideas for students from 9-19 and also has implications for a wider range of students. These are the ideas that really matter, that students get stuck on, and that can be obstacles to future learning. It shows how students learn, why they sometimes get things wrong, and the stre...