- Additional Authors
- Chen, Zhe
- Description
- 1 online resource (394 pages) : digital, PDF file(s).
- Summary
- This authoritative work provides an in-depth treatment of state space methods, with a range of applications in neural and clinical data. Advanced and state-of-the-art research topics are detailed, including topics in state space analyses, maximum likelihood methods, variational Bayes, sequential Monte Carlo, Markov chain Monte Carlo, nonparametric Bayesian, and deep learning methods. Details are provided on practical applications in neural and clinical data, whether this is characterising time series data from neural spike trains recorded from the rat hippocampus, the primate motor cortex, or the human EEG, MEG or fMRI, or physiological measurements of heartbeats or blood pressures. With real-world case studies of neuroscience experiments and clinical data sets, and written by expert authors from across the field, this is an ideal resource for anyone working in neuroscience and physiological data analysis.
- Alternative Title
- Advanced State Space Methods for Neural & Clinical Data
- Subject
- Note
- Title from publisher's bibliographic system (viewed on 09 Dec 2015).
- OCLC
- CR9781139941433
- Title
Advanced State Space Methods for Neural and Clinical Data / Edited by Zhe Chen.
- Publisher
Cambridge : Cambridge University Press, 2015.
- Type of Content
text
- Type of Medium
computer
- Type of Carrier
online resource
- Connect to:
- Added Author
Chen, Zhe, editor.
- Other Form:
Print version: 9781107079199