xxii, 614 pages ; 24 cm
Nonlinear multivariate and time series analysis by neural network methods
β Scribed by William W. Hsieh
- Tongue
- English
- Leaves
- 41
- Category
- Library
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Methods of nonlinear time series analysis are discussed from a dynamical systems perspective on the one hand, and from a statistical perspective on the other. After giving an informal overview of the theory of dynamical systems relevant to the analysis of deterministic time series, time series gener
Methods of nonlinear time series analysis are discussed from a dynamical systems perspective on the one hand, and from a statistical perspective on the other. After giving an informal overview of the theory of dynamical systems relevant to the analysis of deterministic time series, time series gener
Methods of nonlinear time series analysis are discussed from a dynamical systems perspective on the one hand, and from a statistical perspective on the other. After giving an informal overview of the theory of dynamical systems relevant to the analysis of deterministic time series, time series gener
This is the best book for Time Series. It's well written and full of examples and exercises. Chapter 2 and 3 are the difficult parts. You can read them a few times at first. Then after you finish chapter 4-6, come back to read 2 and 3 again and you will grasp a great deal out of it.
<p><P>Increasingly, neural networks are used and implemented in a wide range of fields and have become useful tools in probabilistic analysis and prediction theory. This bookβunique in the literatureβstudies the application of neural networks to the analysis of time series of sea data, namely signif