Mathematical Modeling Of The Learning Curve And Its Practical Applications
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Mathematical Modeling of the Learning Curve
Author: Charles I. Abramson
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2024-06-17
The application of mathematical models in the analysis of learning data has a rich tradition in experimental psychology. Such modeling is not only of scientific interest from psychophysiological point of view but very important from clinical point of view because memory impairment is a common symptom that is frequently diagnosed in elder people, persons after traumatic brain injury, patients with type 2 diabetes mellitus, Parkinson disease, multiple sclerosis, and other neurological and psychiatric diseases. Mild memory impairment might be one of the most important symptoms of a future Alzheimer's disease. Thus, early diagnosis of initial signs of memory impairment is of importance. The book offers the reader hands on practical experience using a mathematical model dveloped by the senior authors. Classroom tested experiments are provided which requires the reader to use the model under various conditions such as learning and memory in both humans and animals. Following an introduction to mathematical models, the book contains 13 experiments. These experiments include those related to animal learning in such organisms as snails, bees, and rats. A variety of human experiments are also presented including those related to short and long term memory, maze learning, classical salivary conditioning, evaluation of sound on memory, and the influence of dietary supplements on memory. We close the section on experiments with and analysis of machine learning curves. Appendices are provided on how to build apparatus and how to install the software.
Mathematical Modeling of the Learning Curve and Its Practical Applications
Author: Igor Igorevich Stepanov
language: en
Publisher: Nova Science Publishers
Release Date: 2022
"This book provides a detailed description of the application of mathematical learning curve modeling to analyze the state of learning and memory in humans and animals. The purpose of the book is to enable the readers to apply the knowledge gained in their own research on learning and memory. The authors hope that the readers may achieve success in this field of knowledge, expand and advance mathematical modeling of the learning curve, and that this book may aid in this process. For this, the authors have developed their own mathematical model based on the systems theory and proved its advantage in relation to those previously proposed. The authors developed MS Windows application "Learning Curve Modeling Tool" to help the reader modeling the learning curve from raw learning data in the California Verbal Learning Test, the Rey Auditory Verbal Learning Test, and other similar memory tests. Moreover, the book describes in detail the Windows and Android application "Memory Monitoring Tool", developed by the authors, which is suited well for mathematical modeling of the learning curves. The application aims to reveal initial signs of memory impairment. Besides, the section APPENDIX A describes a Web application - "Learning curve simulator" - developed by the authors for helping readers to get started with practically modeling the learning curve and testing their memory. This application is included in the book. The book will be useful for undergraduate students, graduate students, advanced graduate students, and professors, especially for professors who work on learning in both humans and animals, and those interested in the memory of marijuana users, alcoholics, and those suffering from diabetes and multiple sclerosis, as well as other neurological and psychological diseases and their neurological complications including those after COVID-19"--
Mathematical Models in Finance
Mathematical Models in Finance compiles papers presented at the Royal Society of London discussion meeting. Topics range from the foundations of classical theory to sophisticated, up-to-date mathematical modeling and analysis. In the wake of the increased level of mathematical awareness in the financial research community, attention has focused on fundamental issues of market modelling that are not adequately allowed for in the standard analyses. Examples include market anomalies and nonlinear coupling effects, and demand new synthesis of mathematical and numerical techniques. This line of inquiry is further stimulated by ever tightening profits due to increased competition. Several papers in this volume offer pointers to future developments in this area.