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020 _a9789811065118
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024 7 _a10.1007/978-981-10-6511-8
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082 0 4 _a621.382
_223
100 1 _aGhosh, Dipak.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_955369
245 1 0 _aMusicality of Human Brain through Fractal Analytics
_h[electronic resource] /
_cby Dipak Ghosh, Ranjan Sengupta, Shankha Sanyal, Archi Banerjee.
250 _a1st ed. 2018.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2018.
300 _aXVII, 232 p. 119 illus., 111 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
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347 _atext file
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_2rda
490 1 _aSignals and Communication Technology,
_x1860-4870
505 0 _aIntroduction -- Methodology -- Emotions from Hindustani Classical Music: An EEG based study with evidence of neural hysteresis -- Musical perception and visual imagery: Do musicians visualize while performing? -- Tanpura drone and brain dynamics: How a simple acoustic signal affects brain rhythms -- In search of universality of music: effect of cross cultural instrumental clips -- Gestalt phenomenon in music: which frequencies do we hear? -- Quantification of musical emotion with neural jitter-shimmer: novel study with hindustani music -- An approach to encapsulate improvisation in hindustani classical music -- Ambiguity in hindustani classical music: development of an automated algorithm to asses ambiguity -- Computing the pitch of an EEG signal: a new paradigm in analysis of bio-signals -- Epilogue.
520 _aThis book provides a comprehensive overview of how fractal analytics can lead to the extraction of interesting features from the complex electroencephalograph (EEG) signals generated by Hindustani classical music. It particularly focuses on how the brain responses to the emotional attributes of Hindustani classical music that have been long been a source of discussion for musicologists and psychologists. Using robust scientific techniques that are capable of looking into the most intricate dynamics of the complex EEG signals, it deciphers the human brain’s response to different ragas of Hindustani classical music, shedding new light on what happens inside the performer’s brain when they are mentally composing the imagery of a particular raga. It also explores the much- debated issue in the musical fraternity of whether there are any universal cues in music that make it identifiable for people throughout the world, and if so, what are the neural correlates associated with the universal cues? This book is of interest to researchers and scholars of music and the brain, nonlinear science, music cognition, music signal processing and music information retrieval. In addition, researchers in the field of nonlinear biomedical signal processing and music signal analysis benefit from this book.  .
650 0 _aSignal processing.
_94052
650 0 _aUser interfaces (Computer systems).
_911681
650 0 _aHuman-computer interaction.
_96196
650 0 _aNeurosciences.
_924499
650 0 _aNeuropsychology.
_931898
650 1 4 _aSignal, Speech and Image Processing .
_931566
650 2 4 _aUser Interfaces and Human Computer Interaction.
_931632
650 2 4 _aNeuroscience.
_934310
650 2 4 _aNeuropsychology.
_931898
700 1 _aSengupta, Ranjan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_955370
700 1 _aSanyal, Shankha.
_eauthor.
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_4http://id.loc.gov/vocabulary/relators/aut
_955371
700 1 _aBanerjee, Archi.
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_4http://id.loc.gov/vocabulary/relators/aut
_955372
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aSignals and Communication Technology,
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_955374
856 4 0 _uhttps://doi.org/10.1007/978-981-10-6511-8
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