top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.
Coherence [[electronic resource] ] : In Signal Processing and Machine Learning / / by David Ramírez, Ignacio Santamaría, Louis Scharf
Coherence [[electronic resource] ] : In Signal Processing and Machine Learning / / by David Ramírez, Ignacio Santamaría, Louis Scharf
Autore Ramirez David
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
Descrizione fisica 1 online resource (495 pages)
Disciplina 006.31
Soggetto topico Signal processing
Computer science - Mathematics
Mathematical statistics
Machine learning
Signal, Speech and Image Processing
Probability and Statistics in Computer Science
Machine Learning
Processament de senyals
Aprenentatge automàtic
Soggetto genere / forma Llibres electrònics
ISBN 3-031-13331-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction -- Historical perspective, motivating problems, and preview of what is to come -- Least Squares and related -- Classical correlations and coherence -- Coherence in the multivariate normal (MVN) model -- Classical tests for correlation -- One-channel matched subspace detectors -- Adaptive subspace detectors -- Two channel matched subspace detectors -- Detection of spatially-correlated time series -- Coherence and the detection of cyclostationarity -- Partial coherence for testing causality -- Subspace averaging -- Coherence and performance bounds -- Variations on coherence -- Conclusion.
Record Nr. UNINA-9910637713703321
Ramirez David  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Coherence [[electronic resource] ] : In Signal Processing and Machine Learning / / by David Ramírez, Ignacio Santamaría, Louis Scharf
Coherence [[electronic resource] ] : In Signal Processing and Machine Learning / / by David Ramírez, Ignacio Santamaría, Louis Scharf
Autore Ramirez David
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
Descrizione fisica 1 online resource (495 pages)
Disciplina 006.31
Soggetto topico Signal processing
Computer science - Mathematics
Mathematical statistics
Machine learning
Signal, Speech and Image Processing
Probability and Statistics in Computer Science
Machine Learning
Processament de senyals
Aprenentatge automàtic
Soggetto genere / forma Llibres electrònics
ISBN 3-031-13331-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction -- Historical perspective, motivating problems, and preview of what is to come -- Least Squares and related -- Classical correlations and coherence -- Coherence in the multivariate normal (MVN) model -- Classical tests for correlation -- One-channel matched subspace detectors -- Adaptive subspace detectors -- Two channel matched subspace detectors -- Detection of spatially-correlated time series -- Coherence and the detection of cyclostationarity -- Partial coherence for testing causality -- Subspace averaging -- Coherence and performance bounds -- Variations on coherence -- Conclusion.
Record Nr. UNISA-996503549103316
Ramirez David  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Communication Principles for Data Science [[electronic resource] /] / by Changho Suh
Communication Principles for Data Science [[electronic resource] /] / by Changho Suh
Autore Suh Changho
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (294 pages)
Disciplina 381
Collana Signals and Communication Technology
Soggetto topico Artificial intelligence—Data processing
Digital media
Computer science—Mathematics
Mathematical statistics
Signal processing
Data Science
Digital and New Media
Probability and Statistics in Computer Science
Signal, Speech and Image Processing
ISBN 981-19-8008-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- Acknowledgements -- Part 1. Communication over the Gaussian channel -- Chapter 1.Overview of the book -- Chapter 2. A statistical model for additive noise channels -- Chapter 3. Additive Gaussian noise model -- Problem Set 1 -- Chapter 4. Optimal receiver: maximum A Posteriori (MAP) principle -- Chapter 5. Analysis of error probability -- Chapter 6. Multiple bits transmission via pulse amplitude modulation -- Problem Set 2 -- Chapter 7. Multi-shot communication -- Chapter 8. Repetition coding -- Chapter 9: Capacity of the additive white Gaussian noise channel -- Problem Set 3 -- Part 2. Communication over inter-symbol interference (ISI) channels -- Chapter 10. Signal conversion from discrete to continuous time (1/2) -- Chapter 11. Signal conversion from discrete to continuous time (2/2) -- Chapter 12. Optimal receiver architecture -- Problem Set 4 -- Chapter 13. Optimal receiver in ISI channels: maximum likelihood (ML) sequence detection -- Chapter 14. Optimal receiver in ISI channels: Viterbi algorithm -- Problem Set 5 -- Chapter 15.Orthogonal frequency division multiplexing (1/3) -- Chapter 16. Orthogonal frequency division multiplexing (2/3) -- Chapter 17. Orthogonal frequency division multiplexing (3/3) -- Problem Set 6 -- Part 3.Data science applications -- Chapter 18. Community detection as a communication problem -- Chapter 19. Community detection: ML principle -- Chapter 20. Community detection: An efficient algorithm -- Chapter 21. Community detection: Python implementation -- Problem Set 7 -- Chapter 22.Haplotype phasing as a communication problem -- Chapter 23. Haplotype phasing: ML principle -- Chapter 24: Haplotype phasing: An efficient algorithm. .
Record Nr. UNINA-9910731488503321
Suh Changho  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Communication Principles for Data Science [[electronic resource] /] / by Changho Suh
Communication Principles for Data Science [[electronic resource] /] / by Changho Suh
Autore Suh Changho
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (294 pages)
Disciplina 381
Collana Signals and Communication Technology
Soggetto topico Artificial intelligence—Data processing
Digital media
Computer science—Mathematics
Mathematical statistics
Signal processing
Data Science
Digital and New Media
Probability and Statistics in Computer Science
Signal, Speech and Image Processing
ISBN 981-19-8008-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- Acknowledgements -- Part 1. Communication over the Gaussian channel -- Chapter 1.Overview of the book -- Chapter 2. A statistical model for additive noise channels -- Chapter 3. Additive Gaussian noise model -- Problem Set 1 -- Chapter 4. Optimal receiver: maximum A Posteriori (MAP) principle -- Chapter 5. Analysis of error probability -- Chapter 6. Multiple bits transmission via pulse amplitude modulation -- Problem Set 2 -- Chapter 7. Multi-shot communication -- Chapter 8. Repetition coding -- Chapter 9: Capacity of the additive white Gaussian noise channel -- Problem Set 3 -- Part 2. Communication over inter-symbol interference (ISI) channels -- Chapter 10. Signal conversion from discrete to continuous time (1/2) -- Chapter 11. Signal conversion from discrete to continuous time (2/2) -- Chapter 12. Optimal receiver architecture -- Problem Set 4 -- Chapter 13. Optimal receiver in ISI channels: maximum likelihood (ML) sequence detection -- Chapter 14. Optimal receiver in ISI channels: Viterbi algorithm -- Problem Set 5 -- Chapter 15.Orthogonal frequency division multiplexing (1/3) -- Chapter 16. Orthogonal frequency division multiplexing (2/3) -- Chapter 17. Orthogonal frequency division multiplexing (3/3) -- Problem Set 6 -- Part 3.Data science applications -- Chapter 18. Community detection as a communication problem -- Chapter 19. Community detection: ML principle -- Chapter 20. Community detection: An efficient algorithm -- Chapter 21. Community detection: Python implementation -- Problem Set 7 -- Chapter 22.Haplotype phasing as a communication problem -- Chapter 23. Haplotype phasing: ML principle -- Chapter 24: Haplotype phasing: An efficient algorithm. .
Record Nr. UNISA-996546820903316
Suh Changho  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Composing Fisher Kernels from Deep Neural Models [[electronic resource] ] : A Practitioner's Approach / / by Tayyaba Azim, Sarah Ahmed
Composing Fisher Kernels from Deep Neural Models [[electronic resource] ] : A Practitioner's Approach / / by Tayyaba Azim, Sarah Ahmed
Autore Azim Tayyaba
Edizione [1st ed. 2018.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Descrizione fisica 1 online resource (69 pages)
Disciplina 515.9
Collana SpringerBriefs in Computer Science
Soggetto topico Pattern recognition
Signal processing
Image processing
Speech processing systems
Information storage and retrieval
Mathematical statistics
Data structures (Computer science)
Artificial intelligence
Pattern Recognition
Signal, Image and Speech Processing
Information Storage and Retrieval
Probability and Statistics in Computer Science
Data Storage Representation
Artificial Intelligence
ISBN 3-319-98524-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1. Kernel Based Learning: A Pragmatic Approach in the Face of New Challenges -- Chapter 2. Fundamentals of Fisher Kernels -- Chapter 3. Training Deep Models and Deriving Fisher Kernels: A Step Wise Approach -- Chapter 4. Large Scale Image Retrieval and Its Challenges -- Chapter 5. Open Source Knowledge Base for Machine Learning Practitioners.
Record Nr. UNINA-9910299348303321
Azim Tayyaba  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Computational Complexity and Property Testing [[electronic resource] ] : On the Interplay Between Randomness and Computation / / edited by Oded Goldreich
Computational Complexity and Property Testing [[electronic resource] ] : On the Interplay Between Randomness and Computation / / edited by Oded Goldreich
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (391 pages) : illustrations
Disciplina 511.352
Collana Theoretical Computer Science and General Issues
Soggetto topico Computer science
Computer engineering
Computer networks
Computer science—Mathematics
Mathematical statistics
Logic programming
Application software
Data structures (Computer science)
Information theory
Theory of Computation
Computer Engineering and Networks
Probability and Statistics in Computer Science
Logic in AI
Computer and Information Systems Applications
Data Structures and Information Theory
ISBN 3-030-43662-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto A Probabilistic Error-Correcting Scheme that Provides Partial Secrecy -- Bridging a Small Gap in the Gap Ampli cation of Assignment Testers -- On (Valiant's) Polynomial-Size Monotone Formula for Majority -- Two Comments on Targeted Canonical Derandomizers -- On the Effect of the Proximity Parameter on Property Testers -- On the Size of Depth-Three Boolean Circuits for Computing Multilinear Functions -- On the Communication Complexity Methodology for Proving Lower Bounds on the Query Complexity of Property Testing -- Super-Perfect Zero-Knowledge Proofs -- On the Relation between the Relative Earth Mover Distance and the Variation Distance (an exposition) -- The Uniform Distribution is Complete with respect to Testing Identity to a Fixed Distribution -- A Note on Tolerant Testing with One-Sided Error -- On Emulating Interactive Proofs with Public Coins -- Reducing Testing Affine Spaces to Testing Linearity of Functions -- Deconstructing 1-Local Expanders -- Worst-case to Average-case Reductions for Subclasses of P -- On the Optimal Analysis of the Collision Probability Tester (an exposition) -- On Constant-Depth Canonical Boolean Circuits for Computing Multilinear Functions -- Constant-Round Interactive Proof Systems for AC0[2] and NC1 -- Flexible Models for Testing Graph Properties -- Pseudo-Mixing Time of Random Walks -- On Constructing Expanders for any Number of Vertices.
Record Nr. UNISA-996418218403316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Computational Complexity and Property Testing [[electronic resource] ] : On the Interplay Between Randomness and Computation / / edited by Oded Goldreich
Computational Complexity and Property Testing [[electronic resource] ] : On the Interplay Between Randomness and Computation / / edited by Oded Goldreich
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (391 pages) : illustrations
Disciplina 511.352
Collana Theoretical Computer Science and General Issues
Soggetto topico Computer science
Computer engineering
Computer networks
Computer science—Mathematics
Mathematical statistics
Logic programming
Application software
Data structures (Computer science)
Information theory
Theory of Computation
Computer Engineering and Networks
Probability and Statistics in Computer Science
Logic in AI
Computer and Information Systems Applications
Data Structures and Information Theory
ISBN 3-030-43662-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto A Probabilistic Error-Correcting Scheme that Provides Partial Secrecy -- Bridging a Small Gap in the Gap Ampli cation of Assignment Testers -- On (Valiant's) Polynomial-Size Monotone Formula for Majority -- Two Comments on Targeted Canonical Derandomizers -- On the Effect of the Proximity Parameter on Property Testers -- On the Size of Depth-Three Boolean Circuits for Computing Multilinear Functions -- On the Communication Complexity Methodology for Proving Lower Bounds on the Query Complexity of Property Testing -- Super-Perfect Zero-Knowledge Proofs -- On the Relation between the Relative Earth Mover Distance and the Variation Distance (an exposition) -- The Uniform Distribution is Complete with respect to Testing Identity to a Fixed Distribution -- A Note on Tolerant Testing with One-Sided Error -- On Emulating Interactive Proofs with Public Coins -- Reducing Testing Affine Spaces to Testing Linearity of Functions -- Deconstructing 1-Local Expanders -- Worst-case to Average-case Reductions for Subclasses of P -- On the Optimal Analysis of the Collision Probability Tester (an exposition) -- On Constant-Depth Canonical Boolean Circuits for Computing Multilinear Functions -- Constant-Round Interactive Proof Systems for AC0[2] and NC1 -- Flexible Models for Testing Graph Properties -- Pseudo-Mixing Time of Random Walks -- On Constructing Expanders for any Number of Vertices.
Record Nr. UNINA-9910409674203321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Computational Intelligence in Music, Sound, Art and Design [[electronic resource] ] : 6th International Conference, EvoMUSART 2017, Amsterdam, The Netherlands, April 19–21, 2017, Proceedings / / edited by João Correia, Vic Ciesielski, Antonios Liapis
Computational Intelligence in Music, Sound, Art and Design [[electronic resource] ] : 6th International Conference, EvoMUSART 2017, Amsterdam, The Netherlands, April 19–21, 2017, Proceedings / / edited by João Correia, Vic Ciesielski, Antonios Liapis
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (X, 371 p. 169 illus.)
Disciplina 005.11
Collana Theoretical Computer Science and General Issues
Soggetto topico Algorithms
Data mining
Artificial intelligence
Computer vision
Computer science—Mathematics
Mathematical statistics
Digital humanities
Data Mining and Knowledge Discovery
Artificial Intelligence
Computer Vision
Probability and Statistics in Computer Science
Digital Humanities
ISBN 3-319-55750-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Algorithmic Songwriting with ALYSIA -- On Symmetry, Aesthetics and Quantifying Symmetrical Complexity -- Towards Polyphony Reconstruction Using Multidimensional Multiple Sequence Alignment -- Melody Retrieval and Classification Using Biologically-Inspired Techniques -- Evolved Aesthetic Analogies to Improve Artistic Experience -- Deep Artificial Composer: A Creative Neural Network Model for Automated Melody Generation -- A Kind of Bio-inspired Learning of mUsic stylE -- Using Autonomous Agents to Improvise Music Compositions in Real-time -- Generating Polyphonic Music Using Tied Parallel Networks -- Mixed-initiative Creative Drawing with webIconoscope -- Clustering Agents for the Evolution of Autonomous Musical Fitness -- EvoFashion: Customising Fashion Through Evolution -- A Swarm Environment for Experimental Performance and Improvisation -- Niche Constructing Drawing Robots -- Automated Shape Design by Grammatical Evolution -- Evolutionary Image Transition Using Random Walks -- Evaluation Rules for Evolutionary Generation of Drum Patterns in Jazz Solos -- Assessing Augmented Creativity: Putting a Lovelace Machine for Interactive Title Generation through a Human Creativity Test -- Play It again: Evolved Audio Effects and Synthesizer Programming -- Fashion Design Aid System with Application of Interactive Genetic Algorithms -- Generalization Performance of Western Instrument Recognition Models in Polyphonic Mixtures with Ethnic Samples -- Exploring the Exactitudes Portrait Series with Restricted Boltzmann Machines -- Evolving Mondrian-Style Artworks -- Predicting Expressive Bow Controls for Violin and Viola. .
Record Nr. UNISA-996466202903316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Computational Intelligence in Music, Sound, Art and Design [[electronic resource] ] : 6th International Conference, EvoMUSART 2017, Amsterdam, The Netherlands, April 19–21, 2017, Proceedings / / edited by João Correia, Vic Ciesielski, Antonios Liapis
Computational Intelligence in Music, Sound, Art and Design [[electronic resource] ] : 6th International Conference, EvoMUSART 2017, Amsterdam, The Netherlands, April 19–21, 2017, Proceedings / / edited by João Correia, Vic Ciesielski, Antonios Liapis
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (X, 371 p. 169 illus.)
Disciplina 005.11
Collana Theoretical Computer Science and General Issues
Soggetto topico Algorithms
Data mining
Artificial intelligence
Computer vision
Computer science—Mathematics
Mathematical statistics
Digital humanities
Data Mining and Knowledge Discovery
Artificial Intelligence
Computer Vision
Probability and Statistics in Computer Science
Digital Humanities
ISBN 3-319-55750-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Algorithmic Songwriting with ALYSIA -- On Symmetry, Aesthetics and Quantifying Symmetrical Complexity -- Towards Polyphony Reconstruction Using Multidimensional Multiple Sequence Alignment -- Melody Retrieval and Classification Using Biologically-Inspired Techniques -- Evolved Aesthetic Analogies to Improve Artistic Experience -- Deep Artificial Composer: A Creative Neural Network Model for Automated Melody Generation -- A Kind of Bio-inspired Learning of mUsic stylE -- Using Autonomous Agents to Improvise Music Compositions in Real-time -- Generating Polyphonic Music Using Tied Parallel Networks -- Mixed-initiative Creative Drawing with webIconoscope -- Clustering Agents for the Evolution of Autonomous Musical Fitness -- EvoFashion: Customising Fashion Through Evolution -- A Swarm Environment for Experimental Performance and Improvisation -- Niche Constructing Drawing Robots -- Automated Shape Design by Grammatical Evolution -- Evolutionary Image Transition Using Random Walks -- Evaluation Rules for Evolutionary Generation of Drum Patterns in Jazz Solos -- Assessing Augmented Creativity: Putting a Lovelace Machine for Interactive Title Generation through a Human Creativity Test -- Play It again: Evolved Audio Effects and Synthesizer Programming -- Fashion Design Aid System with Application of Interactive Genetic Algorithms -- Generalization Performance of Western Instrument Recognition Models in Polyphonic Mixtures with Ethnic Samples -- Exploring the Exactitudes Portrait Series with Restricted Boltzmann Machines -- Evolving Mondrian-Style Artworks -- Predicting Expressive Bow Controls for Violin and Viola. .
Record Nr. UNINA-9910484653603321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Computational Intelligence Methods for Bioinformatics and Biostatistics [[electronic resource] ] : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, Revised Selected Papers / / edited by Andrea Bracciali, Giulio Caravagna, David Gilbert, Roberto Tagliaferri
Computational Intelligence Methods for Bioinformatics and Biostatistics [[electronic resource] ] : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, Revised Selected Papers / / edited by Andrea Bracciali, Giulio Caravagna, David Gilbert, Roberto Tagliaferri
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XXII, 249 p. 98 illus.)
Disciplina 006.3
Collana Lecture Notes in Bioinformatics
Soggetto topico Bioinformatics
Artificial intelligence
Data mining
Computers
Mathematical statistics
Algorithms
Computational Biology/Bioinformatics
Artificial Intelligence
Data Mining and Knowledge Discovery
Computation by Abstract Devices
Probability and Statistics in Computer Science
Algorithm Analysis and Problem Complexity
ISBN 3-319-67834-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910484491503321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui