LEADER 00707nam1 2200265 450 001 990010027670403321 005 20160113142631.0 035 $a001002767 035 $aFED01001002767 035 $a(Aleph)001002767FED01 035 $a001002767 100 $a20160113d2012----km-y0itay50------ba 101 0 $aeng 102 $aGB 105 $a--------001yy 200 1 $a<>sources of social power$fMichel Mann 210 $aCambridge$cCambridge University Press$d2012 610 0 $aPotere$aAspetti sociali$aStoria 676 $a303.3$v22$zita 700 1$aMann,$bMichael$f<1942- > 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990010027670403321 959 $aBFS 997 $aUNINA LEADER 00775nam0-22002651i-450- 001 990001168690403321 035 $a000116869 035 $aFED01000116869 035 $a(Aleph)000116869FED01 035 $a000116869 100 $a20000920d1932----km-y0itay50------ba 101 0 $aeng 200 1 $a<>parallelisme absolu et la theorie unitaire du champ.$fde Cartan Elie. s 210 $aParis$cHermann$d1932 225 1 $aActualités scientifiques et industrielles 300 $aXLIV-V VOL> 700 1$aCartan,$bElie$042832 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990001168690403321 952 $a12-I-3$b171$fMA1 959 $aMA1 996 $aParallelisme absolu et la theorie unitaire du champ$9345609 997 $aUNINA DB $aING01 LEADER 02658nam 2200613 a 450 001 9910461624503321 005 20200520144314.0 010 $a1-84973-275-2 035 $a(CKB)2670000000096417 035 $a(EBL)1185170 035 $a(OCoLC)730289308 035 $a(SSID)ssj0000578382 035 $a(PQKBManifestationID)12198039 035 $a(PQKBTitleCode)TC0000578382 035 $a(PQKBWorkID)10577999 035 $a(PQKB)11469595 035 $a(MiAaPQ)EBC1185170 035 $a(PPN)198470258 035 $a(Au-PeEL)EBL1185170 035 $a(CaPaEBR)ebr10627633 035 $a(CaONFJC)MIL872272 035 $a(EXLCZ)992670000000096417 100 $a20121208d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aAnimal models for neurodegenerative disease$b[electronic resource] /$fedited by Jesu?s Avila, Jose J. Lucas and Fe?lix Herna?ndez 210 $aCambridge [England] $cRSC Pub.$d2011 215 $a1 online resource (307 p.) 225 0$aRSC drug discovery series,$x2041-3203 ;$v6 300 $aDescription based upon print version of record. 311 $a1-84973-184-5 320 $aIncludes bibliographical references and index. 327 $ai-iv; v-viii; ix-xvi; 1-14; 15-38; 39-51; 52-68; 69-85; 86-112; 113-161; 162-176; 177-213; 214-229; 230-250; 251-273; 274-283; 284-290 330 $aIn recent years, medical developments have resulted in an increase in human life expectancy. Some developed countries now have a larger population of individuals aged over 64 than those under 14. One consequence of the ageing population is a higher incidence of certain neurodegenerative disorders. In order to prevent these, we need to learn more about them. This book provides up-to-date information on the use of transgenic mouse models in the study of neurodegenerative disorders such as Alzheimer's and Huntington's disease. By reproducing some of the pathological aspects of the diseases, these 410 0$aRSC Drug Discovery 606 $aNervous system$xDegeneration 606 $aNervous system$xDegeneration$xAnimal models 608 $aElectronic books. 615 0$aNervous system$xDegeneration. 615 0$aNervous system$xDegeneration$xAnimal models. 676 $a616.83 701 $aAvila$b Jesu?s$0994576 701 $aLucas$b Jose? J$0994577 701 $aHerna?ndez$b Fe?lix$0994578 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910461624503321 996 $aAnimal models for neurodegenerative disease$92277644 997 $aUNINA LEADER 01061nam a2200253 i 4500 001 991001911589707536 005 20020503154849.0 008 010510s1991 it ||| | ita 035 $ab10290187-39ule_inst 035 $aEXGIL93545$9ExL 040 $aDip.to Filol. Ling. e Lett.$bita 100 1 $aChiari, Alberto$0149024 245 12$aL'autore della Nencia da Barberino :$bristampa anastatica dell'edizione del 1848 /$cAlberto Chiari, Italiano Marchetti 260 $aFirenze :$bPresso l'Accademia della Crusca,$c1991 300 $a141 p. ;$c25 cm. 650 4$aGiambullari, Bernardo 650 4$aLorenzo : 700 1 $aMarchetti, Italiano$eauthor$4http://id.loc.gov/vocabulary/relators/aut$0393351 907 $a.b10290187$b21-09-06$c27-06-02 912 $a991001911589707536 945 $aLE008 FL.M. (f.r.) 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D: Saggi di ricerca documentaria. 500 $aItaliano, inglese e francese. 500 $aInclude indici 504 $aBibliografia: p. 380-393. 650 4$aMusica$zItalia$zVenezia$ySec. 17.$xStoria e critica$xFonti 650 4$aMusica$zItalia$zVenezia$ySec. 18.$xStoria e critica$xFonti 730 02$aPallade veneta 907 $a.b13526637$b28-01-14$c15-05-07 912 $a991002435499707536 945 $aLE019 A15 MUS B 14$g1$i2019000015394$lle019$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i1445080x$z15-05-07 997 $aUNISALENTO 998 $ale019$b15-05-07$cm$da $e-$fita$git $h0$i0 LEADER 09224nam 2200745Ia 450 001 9910808716103321 005 20200520144314.0 010 $a9786612123047 010 $a9781282123045 010 $a1282123041 010 $a9780470714089 010 $a0470714085 010 $a9780470714072 010 $a0470714077 024 7 $a10.1002/9780470714089 035 $a(CKB)1000000000766498 035 $a(EBL)470306 035 $a(SSID)ssj0000354113 035 $a(PQKBManifestationID)11256478 035 $a(PQKBTitleCode)TC0000354113 035 $a(PQKBWorkID)10302427 035 $a(PQKB)10815223 035 $a(CaBNVSL)mat08040426 035 $a(IDAMS)0b00006485f0ed84 035 $a(IEEE)8040426 035 $a(Au-PeEL)EBL470306 035 $a(CaPaEBR)ebr10307685 035 $a(CaONFJC)MIL212304 035 $a(MiAaPQ)EBC470306 035 $a(OCoLC)352829722 035 $a(PPN)260752851 035 $a(Perlego)2758319 035 $a(EXLCZ)991000000000766498 100 $a20081212d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aDistant speech recognition /$fMatthias Wolfel and John McDonough 205 $a1st ed. 210 $aChichester, West Sussex, U.K. $cWiley$dc2009 215 $a1 online resource (595 p.) 300 $aDescription based upon print version of record. 311 08$a9780470517048 311 08$a0470517042 320 $aIncludes bibliographical references and index. 327 $aForeword -- Preface -- 1 Introduction -- 1.1 Research and Applications in Academia and Industry -- 1.2 Challenges in Distant Speech Recognition -- 1.3 System Evaluation -- 1.4 Fields of Speech Recognition -- 1.5 Robust Perception -- 1.6 Organizations, Conferences and Journals -- 1.7 Useful Tools, Data Resources and Evaluation Campaigns -- 1.8 Organization of this Book -- 1.9 Principal Symbols used Throughout the Book -- 1.10 Units used Throughout the Book -- 2 Acoustics -- 2.1 Physical Aspect of Sound -- 2.2 Speech Signals -- 2.3 Human Perception of Sound -- 2.4 The Acoustic Environment -- 2.5 Recording Techniques and Sensor Configuration -- 2.6 Summary and Further Reading -- 2.7 Principal Symbols -- 3 Signal Processing and Filtering Techniques -- 3.1 Linear Time-Invariant Systems -- 3.2 The Discrete Fourier Transform -- 3.3 Short-Time Fourier Transform -- 3.4 Summary and Further Reading -- 3.5 Principal Symbols -- 4 Bayesian Filters -- 4.1 Sequential Bayesian Estimation -- 4.2 Wiener Filter -- 4.3 Kalman Filter and Variations -- 4.4 Particle Filters -- 4.5 Summary and Further Reading -- 4.6 Principal Symbols -- 5 Speech Feature Extraction -- 5.1 Short-Time Spectral Analysis -- 5.2 Perceptually Motivated Representation -- 5.3 Spectral Estimation and Analysis -- 5.4 Cepstral Processing -- 5.5 Comparison between Mel Frequency, Perceptual LP and warped MVDR Cepstral Coefficient Frontends -- 5.6 Feature Augmentation -- 5.7 Feature Reduction -- 5.8 Feature-Space Minimum Phone Error -- 5.9 Summary and Further Reading -- 5.10 Principal Symbols -- 6 Speech Feature Enhancement -- 6.1 Noise and Reverberation in Various Domains -- 6.2 Two Principal Approaches -- 6.3 Direct Speech Feature Enhancement -- 6.4 Schematics of Indirect Speech Feature Enhancement -- 6.5 Estimating Additive Distortion -- 6.6 Estimating Convolutional Distortion -- 6.7 Distortion Evolution -- 6.8 Distortion Evaluation -- 6.9 Distortion Compensation -- 6.10 Joint Estimation of Additive and Convolutional Distortions. 327 $a6.11 Observation Uncertainty -- 6.12 Summary and Further Reading -- 6.13 Principal Symbols -- 7 Search: Finding the Best Word Hypothesis -- 7.1 Fundamentals of Search -- 7.2 Weighted Finite-State Transducers -- 7.3 Knowledge Sources -- 7.4 Fast On-the-Fly Composition -- 7.5 Word and Lattice Combination -- 7.6 Summary and Further Reading -- 7.7 Principal Symbols -- 8 Hidden Markov Model Parameter Estimation -- 8.1 Maximum Likelihood Parameter Estimation -- 8.2 Discriminative Parameter Estimation -- 8.3 Summary and Further Reading -- 8.4 Principal Symbols -- 9 Feature and Model Transformation -- 9.1 Feature Transformation Techniques -- 9.2 Model Transformation Techniques -- 9.3 Acoustic Model Combination -- 9.4 Summary and Further Reading -- 9.5 Principal Symbols -- 10 Speaker Localization and Tracking -- 10.1 Conventional Techniques -- 10.2 Speaker Tracking with the Kalman Filter -- 10.3 Tracking Multiple Simultaneous Speakers -- 10.4 Audio-Visual Speaker Tracking -- 10.5 Speaker Tracking with the Particle Filter -- 10.6 Summary and Further Reading -- 10.7 Principal Symbols -- 11 Digital Filter Banks -- 11.1 Uniform Discrete Fourier Transform Filter Banks -- 11.2 Polyphase Implementation -- 11.3 Decimation and Expansion -- 11.4 Noble Identities -- 11.5 Nyquist(M) Filters -- 11.6 Filter Bank Design of De Haan et al -- 11.7 Filter Bank Design with the Nyquist(M) Criterion -- 11.8 Quality Assessment of Filter Bank Prototypes -- 11.9 Summary and Further Reading -- 11.10 Principal Symbols -- 12 Blind Source Separation -- 12.1 Channel Quality and Selection -- 12.2 Independent Component Analysis -- 12.3 BSS Algorithms based on Second-Order Statistics -- 12.4 Summary and Further Reading -- 12.5 Principal Symbols -- 13 Beamforming -- 13.1 Beamforming Fundamentals -- 13.2 Beamforming Performance Measures -- 13.3 Conventional Beamforming Algorithms -- 13.4 Recursive Algorithms -- 13.5 Nonconventional Beamforming Algorithms -- 13.6 Array Shape Calibration -- 13.7 Summary and Further Reading. 327 $a13.8 Principal Symbols -- 14 Hands On -- 14.1 Example Room Configurations -- 14.2 Automatic Speech Recognition Engines -- 14.3 Word Error Rate -- 14.4 Single-Channel Feature Enhancement Experiments -- 14.5 Acoustic Speaker-Tracking Experiments -- 14.6 Audio-Video Speaker-Tracking Experiments -- 14.7 Speaker-Tracking Performance vs Word Error Rate -- 14.8 Single-Speaker Beamforming Experiments -- 14.9 Speech Separation Experiments -- 14.10 Filter Bank Experiments -- 14.11 Summary and Further Reading -- Appendices -- A List of Abbreviations -- B Useful Background -- B.1 Discrete Cosine Transform -- B.2 Matrix Inversion Lemma -- B.3 Cholesky Decomposition -- B.4 Distance Measures -- B.5 Super-Gaussian Probability Density Functions -- B.6 Entropy -- B.7 Relative Entropy -- B.8 Transformation Law of Probabilities -- B.9 Cascade of Warping Stages -- B.10 Taylor Series -- B.11 Correlation and Covariance -- B.12 Bessel Functions -- B.13 Proof of the Nyquist / Shannon Sampling Theorem -- B.14 Proof of Equations (11.31 / 11.32) -- B.15 Givens Rotations -- B.16 Derivatives with Respect to Complex Vectors -- B.17 Perpendicular Projection Operators -- Bibliography -- Index. 330 $aA complete overview of distant automatic speech recognition The performance of conventional Automatic Speech Recognition (ASR) systems degrades dramatically as soon as the microphone is moved away from the mouth of the speaker. This is due to a broad variety of effects such as background noise, overlapping speech from other speakers, and reverberation. While traditional ASR systems underperform for speech captured with far-field sensors, there are a number of novel techniques within the recognition system as well as techniques developed in other areas of signal processing that can mitigate the deleterious effects of noise and reverberation, as well as separating speech from overlapping speakers. Distant Speech Recognitionpresents a contemporary and comprehensive description of both theoretic abstraction and practical issues inherent in the distant ASR problem. Key Features: *Covers the entire topic of distant ASR and offers practical solutions to overcome the problems related to it *Provides documentation and sample scripts to enable readers to construct state-of-the-art distant speech recognition systems *Gives relevant background information in acoustics and filter techniques, *Explains the extraction and enhancement of classification relevant speech features *Describes maximum likelihood as well as discriminative parameter estimation, and maximum likelihood normalization techniques *Discusses the use of multi-microphone configurations for speaker tracking and channel combination *Presents several applications of the methods and technologies described in this book *Accompanying website with open source software and tools to construct state-of-the-art distant speech recognition systems This reference will be an invaluable resource for researchers, developers, engineers and other professionals, as well as advanced students in speech technology, signal processing, acoustics, statistics and artificial intelligence fields. 606 $aAutomatic speech recognition 606 $aPattern perception 615 0$aAutomatic speech recognition. 615 0$aPattern perception. 676 $a006.4/54 700 $aWolfel$b Matthias$01117265 701 $aMcDonough$b John$g(John W.)$01671244 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910808716103321 996 $aDistant speech recognition$94186845 997 $aUNINA