How Long to Read A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding

How Long Does it Take to Read A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding?

It takes the average reader 2 hours and 16 minutes to read A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding by Michael C. Burkhart

Assuming a reading speed of 250 words per minute. Learn more

Description

Given a stationary state-space model that relates a sequence of hidden states and corresponding measurements or observations, Bayesian filtering provides a principled statistical framework for inferring the posterior distribution of the current state given all measurements up to the present time. For example, the Apollo lunar module implemented a Kalman filter to infer its location from a sequence of earth-based radar measurements and land safely on the moon. To perform Bayesian filtering, we require a measurement model that describes the conditional distribution of each observation given state. The Kalman filter takes this measurement model to be linear, Gaussian. Here we show how a nonlinear, Gaussian approximation to the distribution of state given observation can be used in conjunction with Bayes’ rule to build a nonlinear, non-Gaussian measurement model. The resulting approach, called the Discriminative Kalman Filter (DKF), retains fast closed-form updates for the posterior. We argue there are many cases where the distribution of state given measurement is better-approximated as Gaussian, especially when the dimensionality of measurements far exceeds that of states and the Bernstein—von Mises theorem applies. Online neural decoding for brain-computer interfaces provides a motivating example, where filtering incorporates increasingly detailed measurements of neural activity to provide users control over external devices. Within the BrainGate2 clinical trial, the DKF successfully enabled three volunteers with quadriplegia to control an on-screen cursor in real-time using mental imagery alone. Participant “T9” used the DKF to type out messages on a tablet PC. Nonstationarities, or changes to the statistical relationship between states and measurements that occur after model training, pose a significant challenge to effective filtering. In brain-computer interfaces, one common type of nonstationarity results from wonkiness or dropout of a single neuron. We show how a robust measurement model can be used within the DKF framework to effectively ignore large changes in the behavior of a single neuron. At BrainGate2, a successful online human neural decoding experiment validated this approach against the commonly-used Kalman filter.

How long is A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding?

A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding by Michael C. Burkhart is 134 pages long, and a total of 34,036 words.

This makes it 45% the length of the average book. It also has 42% more words than the average book.

How Long Does it Take to Read A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding Aloud?

The average oral reading speed is 183 words per minute. This means it takes 3 hours and 5 minutes to read A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding aloud.

What Reading Level is A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding?

A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding is suitable for students ages 10 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

Where Can I Buy A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding?

A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding by Michael C. Burkhart is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.

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