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Latent Variable Analysis and Signal Separation
  • Language: en
  • Pages: 578

Latent Variable Analysis and Signal Separation

  • Type: Book
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  • Published: 2017-02-13
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  • Publisher: Springer

This book constitutes the proceedings of the 13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017, held in Grenoble, France, in Feburary 2017. The 53 papers presented in this volume were carefully reviewed and selected from 60 submissions. They were organized in topical sections named: tensor approaches; from source positions to room properties: learning methods for audio scene geometry estimation; tensors and audio; audio signal processing; theoretical developments; physics and bio signal processing; latent variable analysis in observation sciences; ICA theory and applications; and sparsity-aware signal processing.

Independent Component Analysis and Blind Signal Separation
  • Language: en
  • Pages: 1270

Independent Component Analysis and Blind Signal Separation

  • Type: Book
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  • Published: 2004-10-27
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  • Publisher: Springer

In many situations found both in Nature and in human-built systems, a set of mixed signals is observed (frequently also with noise), and it is of great scientific and technological relevance to be able to isolate or separate them so that the information in each of the signals can be utilized. Blind source separation (BSS) research is one of the more interesting emerging fields now a days in the field of signal processing. It deals with the algorithms that allow the recovery of the original sources from a set of mixtures only. The adjective "blind" is applied because the purpose is to estimate the original sources without any a priori knowledge about either the sources or the mixing system. M...

Independent Component Analysis and Signal Separation
  • Language: en
  • Pages: 864

Independent Component Analysis and Signal Separation

  • Type: Book
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  • Published: 2007-12-20
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  • Publisher: Springer

This book constitutes the refereed proceedings of the 7th International Conference on Independent Component Analysis and Blind Source Separation, ICA 2007, held in London, UK, in September 2007. It covers algorithms and architectures, applications, medical applications, speech and signal processing, theory, and visual and sensory processing.

Handbook of Blind Source Separation
  • Language: en
  • Pages: 856

Handbook of Blind Source Separation

Edited by the people who were forerunners in creating the field, together with contributions from 34 leading international experts, this handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing. Going beyond a machine learning perspective, the book reflects recent results in signal processing and numerical analysis, and includes topics such as optimization criteria, mathematical tools, the design of numerical algorithms, convolutive mixtures, and time...

Advanced Concepts for Intelligent Vision Systems
  • Language: en
  • Pages: 397

Advanced Concepts for Intelligent Vision Systems

This book constitutes the proceedings of the 21st International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2023, held in Kumamoto, Japan, during August 2023. The 31 papers presented in this volume were carefully reviewed and selected from a total of 48 submissions. They were organized in topical sections named: Computer Vision, Affective Computing and Human Interactions, Managing the Biodiversity, Robotics and Drones, Machine Learning.

ICIDC 2023
  • Language: en
  • Pages: 716

ICIDC 2023

The 2023 2nd International Conference on Information Economy, Data Modeling and Cloud Computing (ICIDC 2023) was therefore held during June 2nd to 4th, 2023 in Nanchang, China (hybrid form). The Conference was attended by more than 100 participants and hosted four keynote speeches, more than 60 oral presentations as well as various poster presentations. The proceedings of ICIDC 2023 cover various topics, including Big Data Finance, E-Commerce and Digital Business, Modeling Method, 3D Modeling, Internet of Things, Cloud Computing Platform, etc. All the papers have been checked through rigorous review and processes to meet the requirements of publication. Data modeling allows us to obtain the dynamic change trend of various indicator data, so how to use big data information to model and study the development trend of economic operation plan is of great significance. And that is exactly the purpose of this conference, focusing on the application of big data in the economic field as well as conducting more profound research in combination with cloud computing.

Proceedings
  • Language: en
  • Pages: 760

Proceedings

  • Type: Book
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  • Published: 2000
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  • Publisher: Unknown

None

Independent Component Analysis and Blind Signal Separation
  • Language: en
  • Pages: 1308

Independent Component Analysis and Blind Signal Separation

  • Type: Book
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  • Published: 2004
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  • Publisher: Unknown

None

SSP ...
  • Language: en
  • Pages: 708

SSP ...

  • Type: Book
  • -
  • Published: 2005
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  • Publisher: Unknown

None

Latent Variable Analysis and Signal Separation
  • Language: en
  • Pages: 580

Latent Variable Analysis and Signal Separation

  • Type: Book
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  • Published: 2018-06-05
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  • Publisher: Springer

This book constitutes the proceedings of the 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018, held in Guildford, UK, in July 2018.The 52 full papers were carefully reviewed and selected from 62 initial submissions. As research topics the papers encompass a wide range of general mixtures of latent variables models but also theories and tools drawn from a great variety of disciplines such as structured tensor decompositions and applications; matrix and tensor factorizations; ICA methods; nonlinear mixtures; audio data and methods; signal separation evaluation campaign; deep learning and data-driven methods; advances in phase retrieval and applications; sparsity-related methods; and biomedical data and methods.