muni sankar matam (13 risultati)

Paperback. Condizione: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock.

Condizione: New. pp. 104.

Taschenbuch. Condizione: Neu. An Approach for Device localization using audio fingerprinting based | on Hierarchical Cluster Analysis | Muni Sankar Matam (u. a.) | Taschenbuch | 64 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330033030 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condizione: Neu. Human Activitity Recognition System Using accelerometer and Zigbee | Studies on Human Activity Recognition- Design of Body worn Accelerometer and identify different physical activities | Muni Sankar Matam (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659285929 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Audio fingerprinting is defined as a condensed digital summary to establish the equality or similarity of two audio objects. By comparing the fingerprinting of a query fragment of a few seconds with those stored in a fingerprinting database, the system returns matching results and related metadata. Besides this query-by-example application, this technology can also be used to monitor broadcast and detect copyrighted material. Audio fingerprinting is best known for its ability to link unlabeled audio to corresponding meta-data (e.g. artist and song name), regardless of the audio format. Audio fingerprinting or content-based audio identification (CBID) systems extract a perceptual digest of a piece of audio content, i.e. a fingerprint and store it in a database. When presented with unlabeled audio, its fingerprint is calculated and matched against those stored in the database. For the reader new to analysis of data a very short introduction is now provided on hierarchical clustering. 64 pp. Englisch.

Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Matam Muni SankarMr. M. Muni Sankar received his M.Tech degree in Digital Electronics and communication systems from JNTU, Anantapur, India in 2012. He is currently working as an Assistant Professor in the Department of ECE, SoET, .

Condizione: New. Print on Demand pp. 104 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condizione: New. PRINT ON DEMAND pp. 104.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Matam Muni SankarMr. M. Muni Sankar received his M.Tech degree in Digital Electronics and communication systems from JNTU, Anantapur, India in 2012. After completing Masters degree he has joined as Assistant Professor of ECE at Siddh.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Audio fingerprinting is defined as a condensed digital summary to establish the equality or similarity of two audio objects. By comparing the fingerprinting of a query fragment of a few seconds with those stored in a fingerprinting database, the system returns matching results and related metadata. Besides this query-by-example application, this technology can also be used to monitor broadcast and detect copyrighted material. Audio fingerprinting is best known for its ability to link unlabeled audio to corresponding meta-data (e.g. artist and song name), regardless of the audio format. Audio fingerprinting or content-based audio identification (CBID) systems extract a perceptual digest of a piece of audio content, i.e. a fingerprint and store it in a database. When presented with unlabeled audio, its fingerprint is calculated and matched against those stored in the database. For the reader new to analysis of data a very short introduction is now provided on hierarchical clustering.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Audio fingerprinting is defined as a condensed digital summary to establish the equality or similarity of two audio objects. By comparing the fingerprinting of a query fragment of a few seconds with those stored in a fingerprinting database, the system returns matching results and related metadata. Besides this query-by-example application, this technology can also be used to monitor broadcast and detect copyrighted material. Audio fingerprinting is best known for its ability to link unlabeled audio to corresponding meta-data (e.g. artist and song name), regardless of the audio format. Audio fingerprinting or content-based audio identification (CBID) systems extract a perceptual digest of a piece of audio content, i.e. a fingerprint and store it in a database. When presented with unlabeled audio, its fingerprint is calculated and matched against those stored in the database. For the reader new to analysis of data a very short introduction is now provided on hierarchical clustering.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - With the advent of miniaturized sensing technology, which can be body worn, it is now possible to collect and store data on different aspects of human activities under the conditions of free living. This technology has the potential to be used in automated activity profiling systems which produce a continuous record of bodily activity patterns over extended periods of time. Such activity profiling systems are dependent on recognition algorithms which can effectively interpret body worn sensor data and identify different activities. The automated recognition of bodily activities (stationary, walking, running, jogging) using body worn accelerometer data is a challenging area of work. In this book existing activity recognition system were discussed. In Existing activity recognition systems suffer from several obvious practical limitations such as the location and nature of sensors that people will tolerate. Other issues include ease of use, discretion, cost, and the ability to perform daily activities unimpeded. The results are getting from the Accelerometers with different subjects are collected through pc and can be analysed by Matlab software by activity variance and DT algorithm.