Statistical analysis of neural data : Continuous - space models ( First 2 / 3 )

نویسنده

  • Liam Paninski
چکیده

1 Autoregressive models and Kalman filter models are Gaussian Markov and hidden Markov models, respectively 3 1.1 Example: voltage smoothing and interpolation; inferring biophysical parameters 5 1.2 We may perform inference in the Kalman model either via the forward-backwards recursion or by direct optimization methods . . . . . . . . . . . . . . . . . . . 9 1.3 The Kalman model is only identifiable up to linear transformations of the state variable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.4 Examples: intermittent, noisy, filtered, nonlinearly transformed voltage observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.5 Example: spike sorting given nonstationary data using a mixture-of-Kalmanfilters model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Enhancing Efficiency of Neural Network Model in Prediction of Firms Financial Crisis Using Input Space Dimension Reduction Techniques

The main focus in this study is on data pre-processing, reduction in number of inputs or input space size reduction the purpose of which is the justified generalization of data set in smaller dimensions without losing the most significant data. In case the input space is large, the most important input variables can be identified from which insignificant variables are eliminated, or a variable ...

متن کامل

Advanced Probabilistic Models for Speech and Language

This project proposal applies to the statistical and machine learning models used in speech and language research. It aims to develop a more general theoretical framework for the use of state-space models in speech and language, and to expand the set of models currently used in these fields. Probabilistic Models State-Space Models Generalized SSMs Nonlinear SSMs Bayesian Learning Inferring Traj...

متن کامل

Simulation and Prediction of Wind Speeds: A Neural Network for Weibull

Abstract. Wind as a resource of renewable energy has obtained an important share of the energy market already. Therefore simulation and prediction of wind speeds is essential for both, for engineers and energy traders. In this paper we analyze the surface wind speed data from three prototypic locations: coastal region (Rotterdam), undulating forest landscape few 100 m above sea level(Kassel), ...

متن کامل

Visualizing statistical models: Removing the blindfold

Abstract: Visualization can help in model building, diagnosis, and in developing an understanding about how a model summarizes data. This paper proposes three strategies for visualizing statistical models: (1) display the model in the data space, (2) look at all members of a collection, and (3) explore the process of model fitting, not just the end result. Each strategy is accompanied by exampl...

متن کامل

Converting Continuous-Space Language Models into N-Gram Language Models for Statistical Machine Translation

Neural network language models, or continuous-space language models (CSLMs), have been shown to improve the performance of statistical machine translation (SMT) when they are used for reranking n-best translations. However, CSLMs have not been used in the first pass decoding of SMT, because using CSLMs in decoding takes a lot of time. In contrast, we propose a method for converting CSLMs into b...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009