الصفحة 1
الصفحة 1
Illustrated Pediatric Dentistry ; Part 1
This textbook is modernized with the latest information and techniques in pediatric dentistry. The chapters cover primary pediatric dentistry, its clinical aspects, preventive dentistry, and information about the latest trends in the specialty. The text will equip readers with the knowledge suited to the changing
Fixed prosthodontics for edentulous patients
Fixed prosthodontics, a pivotal branch of restorative dentistry, focuses on the design and application of dental prostheses that are ermanently affixed to the patient’s oral structures. Key considerations in FP include accurate diagnosis, meticulous treatment planning, and precise fabrication of the prosthesis to ensure optimal fit and longevity. This approach not only addresses functional deficits but also improves the overall quality of life for patients by restoring their natural smile and chewing ability.
Blind Speech Separation
This is the first book to provide a cutting edge reference to the fascinating topic of blind source separation (BSS) for convolved speech mixtures. Through contributions by the foremost experts on the subject, the book provides an up-to-date account of research findings, explains the underlying theory, and discusses potential applications. The individual chapters are designed to be tutorial in nature with specific emphasis on an in-depth treatment of state of the art techniques. Blind Speech Separation is divided into three parts:Part 1 presents overdetermined or critically determined BSS. Here the main technology is independent component analysis (ICA). ICA is a statistical method for extracting mutually independent sources from their mixtures. Part 2 addresses underdetermined BSS, where there are fewer microphones than source signals. Here, the sparseness of speech sources is very useful; we can utilize time-frequency diversity, where sources are active in different regions of the time-frequency plane.Part 3 presents monaural BSS where there is only one microphone. Here, we can separate a mixture by using the harmonicity and temporal structure of the sources. We can build a probabilistic framework by assuming a source model, and separate a mixture by maximizing the a posteriori probability of the sources.
