In weniger als einer Minute können Sie mit dem Lesen von Signal Processing for Neuroscientists auf Ihrem Kindle beginnen. Sie haben noch keinen Kindle? Hier kaufen oder mit einer unserer kostenlosen Kindle Lese-Apps sofort zu lesen anfangen.

An Ihren Kindle oder ein anderes Gerät senden

 
 
 

Kostenlos testen

Jetzt kostenlos reinlesen

An Ihren Kindle oder ein anderes Gerät senden

Der Artikel ist in folgender Variante leider nicht verfügbar
Keine Abbildung vorhanden für
Farbe:
Keine Abbildung vorhanden
 

Signal Processing for Neuroscientists: An Introduction to the Analysis of Physiological Signals [Kindle Edition]

Wim van Drongelen
5.0 von 5 Sternen  Alle Rezensionen anzeigen (1 Kundenrezension)

Kindle-Preis: EUR 60,65 Inkl. MwSt. und kostenloser drahtloser Lieferung über Amazon Whispernet

Kostenlose Kindle-Leseanwendung Jeder kann Kindle Bücher lesen  selbst ohne ein Kindle-Gerät  mit der KOSTENFREIEN Kindle App für Smartphones, Tablets und Computer.

Geben Sie Ihre E-Mail-Adresse oder Mobiltelefonnummer ein, um die kostenfreie App zu beziehen.

Weitere Ausgaben

Amazon-Preis Neu ab Gebraucht ab
Kindle Edition EUR 60,65  
Gebundene Ausgabe EUR 83,41  
Taschenbuch --  


Produktbeschreibungen

Kurzbeschreibung

Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the ‘golden trio’ in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®.

* Multiple color illustrations are integrated in the text
* Includes an introduction to biomedical signals, noise characteristics, and recording techniques
* Basics and background for more advanced topics can be found in extensive notes and appendices
* A Companion Website hosts the MATLAB scripts and several data files:
   http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670

Synopsis

"Signal Processing for Neuroscientists" introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the golden trio in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB[registered].

Multiple color illustrations are integrated in the text. It includes an introduction to biomedical signals, noise characteristics, and recording techniques. Basics and background for more advanced topics can be found in extensive notes and appendices.


Produktinformation


Mehr über den Autor

Entdecken Sie Bücher, lesen Sie über Autoren und mehr

Kundenrezensionen

4 Sterne
0
3 Sterne
0
2 Sterne
0
1 Sterne
0
5.0 von 5 Sternen
5.0 von 5 Sternen
Die hilfreichsten Kundenrezensionen
1 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Pretty good book for the basics 8. Oktober 2008
Format:Gebundene Ausgabe|Verifizierter Kauf
This is an excellent book for the basics. As a non-mathematician, it was really useful to me. With its many figures and explanations it helps to understand the equations and doesn't just give them and proof them as many books in this field do. Its chapters about Fourier transform, averaging, Laplace and z-Transform and digital filters are really well written. Also this book will help the average human being to understand wavelet transforms. The only drawback of the book is that it covers really just the basics. You might have a problem of which you think that it's simple but the book might still not cover it. This is for example true for the Hilbert transform.
War diese Rezension für Sie hilfreich?
Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)
Amazon.com: 3.6 von 5 Sternen  5 Rezensionen
6 von 6 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Fills an important niche 15. Februar 2010
Von Marc Benayoun - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
This book is clearly not intended for the beginner. It is intended for graduate students or undergraduates with a good working knowledge of at least calculus although many people benefit from previous exposure to differential equations in reading this book. There are many books out there in the math and physics literature that cover many of these topics but are entirely incomprehensible to the average neuroscientist. This book is the only book on the market that bridges the knowledge gap between students who already possess an introductory quantitative background and those capable of reading modern quantitative literature from fields such as engineering and signal processing. It is also the only book for neuroscientists that introduces these more advanced concepts from the perspective of a neuroscience (i.e. using EEG recordings, etc. to illustrate the methodology). Finally, the Matlab code presented in the book can in many instances be used directly in one's own research making this book a very practical investment.
5 von 5 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Useful. 17. Mai 2008
Von High Definition - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe|Verifizierter Kauf
This book contains useful exercises and demonstrations of MATLAB code that are worth looking at. Overall, I think it covers the major topics and does a decent job fulfilling that purpose.

Having said that, however, the language of the book is not reader-friendly. It's not to say that we aren't dealing with advanced material here, because it wasn't intended for the beginner. Don't expect that you'll just be able to pick up the text and read it without any prior knowledge.

I would have given this book an additional star, however, there are some errors of calculation in the beginning exercises. If you are the advanced reader, you'll pick up on these--someone other than myself actually picked up on these, so don't just take the calculation and their end result to be the answer--as always, be cautious when you read.
2 von 2 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen May be difficult for novices 24. März 2009
Von Gradgirl - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
As a new user to Matlab, I found this book too challenging to be effective.
1 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Outstanding if you're up on your ODEs 24. August 2013
Von Let's Compare Options Preptorial - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe|Verifizierter Kauf
I'm an EE who writes domain specific languages for robotics, and also works in medical devices. I've worked in Neuro a LOT but am not a Neurologist. From an Engineering viewpoint, signal processing is about analyzing, transforming and designing time and/or frequency based signals. The two major "divisions" of the field include analog and digital. The major "tools" are advanced statistics (read: sampling), transforms and filters.

This book attempts to put mostly DSP in biological frames with EEG type examples for the harmonics. If you're either a neuro person who is up on ordinary differential equations (a little pdes don't hurt), or you've taken EE courses in SP, you will LOVE this text. In an ironic sense, biological neural and synaptic nets are "sortof" analog, whereas SP is now heavily digital. Over a decade ago some of Neurology started to analyze spiking and other neuronal systems via dynamical systems models-- meaning differential equations, and if you're a part of that group, this book will be wonderful for you.

If you are very rusty on calculus, haven't done any linear algebra, and no ODEs/PDEs, and especially if you're an autodidact, I'd pick up one of the inexpensive Dover intros to Fourier transforms, odes and pdes before tackling this. You can get some of these for as little as $3 US. BTW, this book also has a number of amazing new and used "deals" and I've seen it new for as low as $35 US, so SHOP it, especially via Amazon third parties and at Abe Books.

I worked at GE in MRI and NMR for a while and took a number of neural imaging physics classes. In addition to the signal processing features of neural rhythms and spikes themselves, many measurement and research technologies are also SP based, eg. ASP- RF in the case of MRI. Matlab or its GNU free version are musts for those studies, and this fine text. Again, if you haven't worked with Matlab, you won't learn it with this text, and will get lost quickly. There are a number of inexpensive Matlab books, one specifically for neuro (MATLAB for Neuroscientists, Second Edition: An Introduction to Scientific Computing in MATLAB) if you find it used, and you'll need to brush up on the user interface. There are many online tutorials on it, and numerous books on the GNU version here on Amazon also.

If you can't find a good Matlab prep text, this is the best one I've read, used and found that is up to date and reasonably priced: Matlab, Third Edition: A Practical Introduction to Programming and Problem Solving. You don't really need the "neuro" version if you get Dr. Stormy's fine text.

The Matlab code in this text is at about 95% usable right out of the book. That is astonishing for a text, and some of the code runs the first time! Unheard of in most of the texts you get today that are rushed to press. Highly recommended with the right background or pre-reading/ supplementary prep.
1 von 3 Kunden fanden die folgende Rezension hilfreich
1.0 von 5 Sternen This book was of very low quality. 7. Dezember 2012
Von Michael Van Deelen - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe|Verifizierter Kauf
This book appeared to have some good information in it, especially the discussion of signal transforms. However, many of the charts and diagrams were very poor. The illustrations and printing in them were often so small as to be unintelligible. I was so disappointed in the quality of the book that I returned it.
Waren diese Rezensionen hilfreich?   Wir wollen von Ihnen hören.
Kundenrezensionen suchen
Nur in den Rezensionen zu diesem Produkt suchen

Kunden diskutieren

Das Forum zu diesem Produkt
Diskussion Antworten Jüngster Beitrag
Noch keine Diskussionen

Fragen stellen, Meinungen austauschen, Einblicke gewinnen
Neue Diskussion starten
Thema:
Erster Beitrag:
Eingabe des Log-ins
 

Kundendiskussionen durchsuchen
Alle Amazon-Diskussionen durchsuchen
   


Ähnliche Artikel finden