Beginning with a simple model of the debt/equity impact upon firm value and progressively adding complexity to this model, this book seeks to answer the question, What is the frontier of knowledge with respect to debt/equity alternatives, and could a major paradigm shift affect debt/equity choices? With a view toward providing the reader with a framework for examining debt/equity decisions, this book begins with a simple model of the debt/equity impact upon firm value. Utilizing the paradigm development of capital structure theory to identify the current research frontier of the factors affecting the firm debt/equity position, the authors also extrapolate from the current frontier to outline future opportunities for research and improvements in capital structure analysis. Each chapter begins with a discussion of a central tenet, moves on to a discussion of the theoretical research and empirical evidence pertaining to the tenet, and concludes with a summary of the implications of the paradigm shift for current and future research and practice. A chapter at the end of the book provides an analysis of some unanswered questions in the current frontier of knowledge that may be exploited for further research. One is the strength of signaling of capital structure changes on firm value. A second is a lack of specification for the set of capital structure simultaneous equations. A third emerging issue is the definition of the capital structure within behavioral finance thinking.
The signal processing (SP) landscape has been enriched by recent advances in artificial intelligence (AI) and machine learning (ML), yielding new tools for signal estimation, classification, prediction, and manipulation. Layered signal representations, nonlinear function approximation and nonlinear signal prediction are now feasible at very large scale in both dimensionality and data size. These are leading to significant performance gains in a variety of long-standing problem domains like speech and Image analysis. As well as providing the ability to construct new classes of nonlinear functions (e.g., fusion, nonlinear filtering). This book will help academics, researchers, developers, graduate and undergraduate students to comprehend complex SP data across a wide range of topical application areas such as social multimedia data collected from social media networks, medical imaging data, data from Covid tests etc. This book focuses on AI utilization in the speech, image, communications and yirtual reality domains.
This will help us customize your experience to showcase the most relevant content to your age group
Please select from below
Login
Not registered?
Sign up
Already registered?
Success – Your message will goes here
We'd love to hear from you!
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.