Computational Information Geometry (Signals and Communication Technology)

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Publisher ‏ : ‎ Springer; 1st ed. 2017 edition (December 1, 2016)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 320 pages
ISBN-10 ‏ : ‎ 3319470566
ISBN-13 ‏ : ‎ 978-3319470566
Item Weight ‏ : ‎ 1.38 pounds
Dimensions ‏ : ‎ 6.14 x 0.94 x 9.21 inches

Computational Information Geometry: Understanding Signals and Communication Technology

In the world of signals and communication technology, the field of computational information geometry plays a crucial role in understanding and analyzing complex data structures and patterns. By combining principles from information theory, differential geometry, and machine learning, computational information geometry provides a powerful framework for extracting meaningful insights from noisy and high-dimensional data.

One of the key concepts in computational information geometry is the notion of measuring distances and similarities between data points in a geometric space. By representing data as points in a high-dimensional space, researchers can apply geometric techniques to analyze the underlying structure and relationships within the data. This allows for the development of efficient algorithms for tasks such as clustering, classification, and dimensionality reduction.

Another important aspect of computational information geometry is the use of information-theoretic measures to quantify the amount of information contained in data sets. By applying concepts such as entropy, mutual information, and divergence, researchers can gain a deeper understanding of the underlying patterns and dependencies in the data. This can lead to the development of more accurate models and algorithms for tasks such as data compression, signal processing, and communication.

Overall, computational information geometry offers a powerful set of tools for analyzing and interpreting complex data in the field of signals and communication technology. By leveraging principles from information theory and differential geometry, researchers can develop innovative solutions to a wide range of problems in areas such as image processing, speech recognition, and wireless communication. As technology continues to advance, computational information geometry will play an increasingly important role in shaping the future of signal processing and communication systems.
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