The Stationary Phase Approximation, Time-Frequency Decomposition and Auditory Processing
The principle of stationary phase (PSP) is re-examined in the context of linear time-frequency (TF) decomposition using Gaussian, gammatone and gamma chirp filters at uniform, logarithmic and cochlear spacings in frequency. This necessitates consideration of the use the PSP on non-asymptotic integra...
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Veröffentlicht in: | IEEE transactions on signal processing 2014-01, Vol.62 (1), p.56-68 |
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description | The principle of stationary phase (PSP) is re-examined in the context of linear time-frequency (TF) decomposition using Gaussian, gammatone and gamma chirp filters at uniform, logarithmic and cochlear spacings in frequency. This necessitates consideration of the use the PSP on non-asymptotic integrals and leads to the introduction of a test for phase rate dominance. Regions of the TF plane that pass the test and do not contain stationary phase points contribute little or nothing to the final output. Analysis values that lie in these regions can thus be set to zero, i.e., sparsity. In regions of the TF plane that fail the test or are in the vicinity of stationary phase points, synthesis is performed in the usual way. A new interpretation of the location parameters associated with the synthesis filters leads to: i) a new method for locating stationary phase points in the TF plane and ii) a test for phase rate dominance in that plane. Together this is a TF stationary phase approximation (TFSPA) for both analysis and synthesis. The stationary phase regions of several elementary signals are identified theoretically and examples of reconstruction given. An analysis of the TF phase rate characteristics for the case of two simultaneous tones predicts and quantifies a form of simultaneous masking similar to that which characterizes the auditory system. |
doi_str_mv | 10.1109/TSP.2013.2284479 |
format | Article |
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This necessitates consideration of the use the PSP on non-asymptotic integrals and leads to the introduction of a test for phase rate dominance. Regions of the TF plane that pass the test and do not contain stationary phase points contribute little or nothing to the final output. Analysis values that lie in these regions can thus be set to zero, i.e., sparsity. In regions of the TF plane that fail the test or are in the vicinity of stationary phase points, synthesis is performed in the usual way. A new interpretation of the location parameters associated with the synthesis filters leads to: i) a new method for locating stationary phase points in the TF plane and ii) a test for phase rate dominance in that plane. Together this is a TF stationary phase approximation (TFSPA) for both analysis and synthesis. The stationary phase regions of several elementary signals are identified theoretically and examples of reconstruction given. 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This necessitates consideration of the use the PSP on non-asymptotic integrals and leads to the introduction of a test for phase rate dominance. Regions of the TF plane that pass the test and do not contain stationary phase points contribute little or nothing to the final output. Analysis values that lie in these regions can thus be set to zero, i.e., sparsity. In regions of the TF plane that fail the test or are in the vicinity of stationary phase points, synthesis is performed in the usual way. A new interpretation of the location parameters associated with the synthesis filters leads to: i) a new method for locating stationary phase points in the TF plane and ii) a test for phase rate dominance in that plane. Together this is a TF stationary phase approximation (TFSPA) for both analysis and synthesis. The stationary phase regions of several elementary signals are identified theoretically and examples of reconstruction given. An analysis of the TF phase rate characteristics for the case of two simultaneous tones predicts and quantifies a form of simultaneous masking similar to that which characterizes the auditory system.</description><subject>Applied sciences</subject><subject>Approximation methods</subject><subject>Auditory system</subject><subject>Bandwidth</subject><subject>Chirp</subject><subject>cochlear filters</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Exact sciences and technology</subject><subject>Frequency response</subject><subject>gammachirp</subject><subject>gammatone</subject><subject>Information, signal and communications theory</subject><subject>Method of reassignment</subject><subject>Prototypes</subject><subject>Signal and communications theory</subject><subject>Signal, noise</subject><subject>simultaneous masking</subject><subject>Telecommunications and information theory</subject><subject>Time-frequency analysis</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><recordid>eNo9kM1Lw0AQxRdRsFbvgpdcvJm635s9ltqqULDQCL2F7WbWrrRJ3E3B_vcmtvQyM8x7v2F4CN0TPCIE6-d8uRhRTNiI0oxzpS_QgGhOUsyVvOxmLFgqMrW6RjcxfmNMONdygFb5BpJla1pfVyYcksXGREjGTRPqX7_7Xz8lud9BOgvws4fKHpIXsPWuqaPv1cRUZTLel76tezzUFmL01dctunJmG-Hu1IfoczbNJ2_p_OP1fTKep5Yx0aZKrsu1EDYT3GYZN444C9wpBqJUVDqgyq0xsVaVoJwijnGpCZFOGqZ5V4YIH-_aUMcYwBVN6B4Ph4Lgok-m6JIp-mSKUzId8nhEGhOt2bpgKuvjmaMZxYzrrPM9HH0eAM6ylBRrodgfJ_duHQ</recordid><startdate>20140101</startdate><enddate>20140101</enddate><creator>Mulgrew, Bernard</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20140101</creationdate><title>The Stationary Phase Approximation, Time-Frequency Decomposition and Auditory Processing</title><author>Mulgrew, Bernard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c335t-76bdb55c854c884af1fce4f73e5d726fe27fb01cc7de7f71f3469116f6a3946a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Applied sciences</topic><topic>Approximation methods</topic><topic>Auditory system</topic><topic>Bandwidth</topic><topic>Chirp</topic><topic>cochlear filters</topic><topic>Detection, estimation, filtering, equalization, prediction</topic><topic>Exact sciences and technology</topic><topic>Frequency response</topic><topic>gammachirp</topic><topic>gammatone</topic><topic>Information, signal and communications theory</topic><topic>Method of reassignment</topic><topic>Prototypes</topic><topic>Signal and communications theory</topic><topic>Signal, noise</topic><topic>simultaneous masking</topic><topic>Telecommunications and information theory</topic><topic>Time-frequency analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mulgrew, Bernard</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><jtitle>IEEE transactions on signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mulgrew, Bernard</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Stationary Phase Approximation, Time-Frequency Decomposition and Auditory Processing</atitle><jtitle>IEEE transactions on signal processing</jtitle><stitle>TSP</stitle><date>2014-01-01</date><risdate>2014</risdate><volume>62</volume><issue>1</issue><spage>56</spage><epage>68</epage><pages>56-68</pages><issn>1053-587X</issn><eissn>1941-0476</eissn><coden>ITPRED</coden><abstract>The principle of stationary phase (PSP) is re-examined in the context of linear time-frequency (TF) decomposition using Gaussian, gammatone and gamma chirp filters at uniform, logarithmic and cochlear spacings in frequency. This necessitates consideration of the use the PSP on non-asymptotic integrals and leads to the introduction of a test for phase rate dominance. Regions of the TF plane that pass the test and do not contain stationary phase points contribute little or nothing to the final output. Analysis values that lie in these regions can thus be set to zero, i.e., sparsity. In regions of the TF plane that fail the test or are in the vicinity of stationary phase points, synthesis is performed in the usual way. A new interpretation of the location parameters associated with the synthesis filters leads to: i) a new method for locating stationary phase points in the TF plane and ii) a test for phase rate dominance in that plane. Together this is a TF stationary phase approximation (TFSPA) for both analysis and synthesis. The stationary phase regions of several elementary signals are identified theoretically and examples of reconstruction given. An analysis of the TF phase rate characteristics for the case of two simultaneous tones predicts and quantifies a form of simultaneous masking similar to that which characterizes the auditory system.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/TSP.2013.2284479</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Applied sciences Approximation methods Auditory system Bandwidth Chirp cochlear filters Detection, estimation, filtering, equalization, prediction Exact sciences and technology Frequency response gammachirp gammatone Information, signal and communications theory Method of reassignment Prototypes Signal and communications theory Signal, noise simultaneous masking Telecommunications and information theory Time-frequency analysis |
title | The Stationary Phase Approximation, Time-Frequency Decomposition and Auditory Processing |
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