الصفحة 1
الصفحة 1
New Methods of Concurrent Checking
New Methods of Concurrent Checking is the ultimate reference to answer the question as to how the best possible state-of-the-art error detection circuits can be designed. The most effective methods of concurrent checking for digital circuits are comprehensively described which were developed in the last 15 years. Some of the methods are published for the first time. How concurrent checking can be combined with soft error correction is also shown for the first time. This book is invaluable in considering the design of reliable systems in the emerging Nanotechnologies with an associated growing number of transient faults.
Error Correction Codes for Non-Volatile Memories
In ECC for Non-Volatile Memories the authors expose the basics of coding theory needed to understand the application to memories, as well as the relevant design topics, with reference to both NOR and NAND Flash architectures. A collection of software routines is also included for better understanding.
English proofreader
Using Natural Language Processing via Deep Learning, we will attempt to implement a context-sensitive spelling error correction system focused on casual text messaging. For example, usual autocorrect systems will not correct a sentence like “An apple is better than a banana” as this is a syntactically correct sentence. However, a correction should be made here to the word “then” and the sentence should be, “An apple is better than a banana.” These types of mistakes are common in people texting and can be found for example in people learning English as a second language. Natural Language Processing can be summarized as combining the utilization of computation to understand the concepts of natural language and speech.
Machine Learning for Multimodal Interaction ; 5th International Workshop, MLMI 2008, Utrecht, The Netherlands, September 8-10, 2008. Proceedings
The 12 revised full papers and 15 revised poster papers presented together with 5 papers of a special session on user requirements and evaluation of multimodal meeting browsers/assistants were carefully reviewed and selected from 47 submissions. The papers cover a wide range of topics related to human-human communication modeling and processing, as well as to human-computer interaction, using several communication modalities. Special focus is given to the analysis of non-verbal communication cues and social signal processing, the analysis of communicative content, audio-visual scene analysis, speech processing, interactive systems and applications.
Machine Learning for Multimodal Interaction ; 4th International Workshop, MLMI 2007, Brno, Czech Republic, June 28-30, 2007, Revised Selected Papers
This book contains a selection of revised papers from the 4th Workshop on Machine Learning for Multimodal Interaction (MLMI 2007), which took place in Brno, Czech Republic, during June 28 30, 2007. As in the previous editions of the MLMI series, the 26 chapters of this book cover a large area of topics, from multimodal processing and human computer interaction to video, audio, speech and language processing. The application of machine learning techniques to problems arising in these felds and the design and analysis of software
