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Information and Communication Theory-Source Coding Techniques-Part II
This handbook covers basic concepts of Information and mathematical theory that deals with the fundamental aspects of communication systems. The purpose of this Hand-Book is to develop the foundation ideas of information theory and to indicate where and how the theory can be applied in a real-time scenario and applications. The Handbook is categorized into two parts (PART - I & PART - II) The objectivesof this Handbook is to Explain the concepts of information source and entropy, Demonstrate the working of various Encoding Techniques, Discuss various source encoding algorithms, Illustrate the use of Cyclic and convolution codes. The readers reliability from this Handbook is to Build the basic concepts of information source and measure of information, Apply different Encoding Schemes for given applications, Develop the different Source Encoding Algorithm for given applications.
Handbook on Information and Communication Theory - Fundamental Approaches & Techniques - Part I
This handbook covers basic concepts of Information and mathematical theory that deals with the fundamental aspects of communication systems. The purpose of this Hand-Book is to develop the foundation ideas of information theory and to indicate where and how the theory can be applied in a real-time scenario and applications. The Handbook is categorized into two parts (PART - I & PART - II) The objectivesof this Handbook is to Explain the concepts of information source and entropy, Demonstrate the working of various Encoding Techniques, Discuss various source encoding algorithms, Illustrate the use of Cyclic and convolution codes. The readers reliability from this Handbook is to Build the basic concepts of information source and measure of information, Apply different Encoding Schemes for given applications, Develop the different Source Encoding Algorithm for given applications.
Reinforcement Learning - Principles, Concepts and Applications
Reinforcement learning (RL) is a subfield of machine learning that deals with how an agent should learn to take actions in an environment to maximize some notion of cumulative reward. In other words, reinforcement learning is a learning paradigm where an agent learns to interact with an environment by taking actions and observing the feedback it receives in the form of rewards or penalties. It is a feedback-based Machine learning technique in which an agent learns to behave in an environment by performing the actions and seeing the results of actions. For each good action, the agent gets positive feedback, and for each bad action, the agent gets negative feedback or penalty.
Artificial Intelligence: Practical Approach
The book introduces programming concepts through Python language. The simple syntax of Python makes it an ideal choice for learning programming. Because of the availability of extensive standard libraries and third-party support, it is rapidly evolving as the preferred programming language among the application developers. It will bolster your foundational skills in Artificial Intelligence. Make the most of our Expert Mentor-ship facility and gain a practical understanding of Artificial Intelligence and Machine Learning. Make the most of our real-world projects from diverse industries. The content in this book goes a long way towards helping you unlock lucrative career opportunities in the c...
ICASISET 2020
We are delighted to introduce the proceedings of the first edition of the 2020 European Alliance for Innovation (EAI) International Conference on Advanced Scientific Innovation in Science, Engineering and Technology. This conference has brought innovative academics, industrial experts researchers, developers and practitioners around the world in the field of Science, Engineering and Technology to a common forum. The technical program of ICASISET 2020 consisted of 97 full papers, including 6 invited papers in oral presentation sessions at the main conference tracks. The conference tracks were: Innovative Computing, Advanced innovation technology in Communication, Industry automation, hydrogen...
High Performance Computing, Smart Devices and Networks
This book comprises the proceedings of the 3rd International Conference on Computer Vision, High-Performance Computing, Smart Devices, and Networks (CHSN 2022). This book highlights high-quality research articles in machine learning, computer vision, and networks. The content of this volume gives the reader an up-to-date picture of the state-of-the-art connection between computational intelligence, machine learning, and IoT. The papers in this volume are peer-reviewed by experts in related areas. The book will serve as a valuable reference resource for academics and researchers across the globe.
Big Data Analytics and Cloud Computing
Big data analytics and cloud computing is the fastest growing technologies in current era. This text book serves as a purpose in providing an understanding of big data principles and framework at the beginner?s level. The text book covers various essential concepts of big-data analytics and processing tools such as HADOOP and YARN. The Textbook covers an analogical understanding on bridging cloud computing with big-data technologies with essential cloud infrastructure protocol and ecosystem concepts. PART I: Hadoop Distributed File System Basics, Running Example Programs and Benchmarks, Hadoop MapReduce Framework Essential Hadoop Tools, Hadoop YARN Applications, Managing Hadoop with Apache A...
Deep Learning for Smart Healthcare
Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data. Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new w...
Deep Learning
In a very short time, deep learning has become a widely useful technique, solving and automating problems in computer vision, robotics, healthcare, physics, biology, and beyond. One of the delightful things about deep learning is its relative simplicity. Powerful deep learning software has been built to make getting started fast and easy. In a few weeks, you can understand the basics and get comfortable with the techniques. This opens up a world of creativity. You start applying it to problems that have data at hand, and you feel wonderful seeing a machine solving problems for you. However, you slowly feel yourself getting closer to a giant barrier. You built a deep learning model, but it do...
