Source Separation and Machine Learning - Jen-Tzung Chien
-30% ar kodu BOOKS
Piegāde 10-16 darba dienu laikā
30 dienu atgriešanas politika
Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It illustrates how BSS problems are tackled through adaptive learning algorithms and model-based approaches using the latest information on mixture signals to build a BSS model that is seen as a statistical model fo ... Pilns apraksts
Jums varētu patikt arī
TOP
If Anyone Builds It, Everyone Dies: The Case Against Superintelligent AI
Eliezer Yudkowsky, Nate Soares
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Open Circuits: The Inner Beauty of Electronic Components
Eric Schlaepfer, Windell Oskay
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Get started with MicroPython on Raspberry Pi Pico: The Official Raspberry Pi Pico Guide
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Practical Electronics for Inventors
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Nucleo Boards Programming with the STM32CubeIDE: Hands-on in more than 50 projects
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
Steven L. Brunton, J. Nathan Kutz
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Fundamentals of Aerodynamics ISE
Christopher Cadou, John D. Anderson
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Black Holes: The Key to Understanding the Universe
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
KiCad Like A Pro - Fundamentals and Projects: Getting started with the world's best open-source PCB tool
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Foundations of Flavor: The Noma Guide to Fermentation: Including Step-By-Step Information on Making and Cooking with: Koji, Kombuchas, Shoyus, Misos, Vinegars, Garums, Lacto-Ferments and black Fruits Vegetables
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Make: Electronics: Learning by Discovery: A hands-on primer for the new electronics enthusiast
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Learning the Art of Electronics: A Hands-On Lab Course
Thomas C. Hayes, Paul Horowitz, David Abrams
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Arduino UNO Q and AI: Learn to Build Intelligent Embedded Systems
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Idea Factory: Bell Labs and the Great Age of American Innovation
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Flowers For Algernon: A Modern Literary Classic
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Collection of Exercises for PLC Programming: 100 programming exercises from beginner to expert level
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Professional SMD Assembly: Practical Low-Cost Methods for Reliable PCB Production
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Blood in the Machine: The Origins of the Rebellion Against Big Tech
-30% ar kodu BOOKS
Piegādātāja noliktavā
Aprašymas
Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It illustrates how BSS problems are tackled through adaptive learning algorithms and model-based approaches using the latest information on mixture signals to build a BSS model that is seen as a statistical model for a whole system. Looking at different models, including independent component analysis (ICA), nonnegative matrix factorization (NMF), nonnegative tensor factorization (NTF), and deep neural network (DNN), the book addresses how they have evolved to deal with multichannel and single-channel source separation.
Vairāk informācijas
| Autors | Jen-Tzung Chien |
|---|---|
| Izdevējs | Elsevier Science |
| Izlaides gads | 2018 |
| Vāka tips | Mīkstais vāks |
| EAN | 9780128177969 |