In this post, we share some recent promising results regarding the applications of Deep Learning in analog IC design. While this work targets a specific application, the proposed methods can be used ...

This paper develops a parameter-expanded Monte Carlo EM (PX-MCEM) algorithm to perform maximum likelihood estimation in a multivariate sample selection model. In contrast to the current methods of ...

For instance, consider the "Learn the Topology" algorithm defined in learn.py and see how these three elements are declared. All events have a field target of type Pid. This indicates which process ...

High-precision source localization depends on many factors, including a suitable location method. Beamforming-based methods, such as the steered response power (SRP), are a common type of acoustic ...

Abstract: KNN algorithm is one of the most classical algorithms in machine learning algorithms. This paper focused on the problems of large training sets and differences in sample feature numbers.

This is a basic code simulation made out of basic javascript to simulate how an area in a pixel grid is filled using Boundary Fill algorithm. Reference : https://www ...

Abstract: The two-speed rotation vector-based attitude update in Strap-down Inertial Navigation System algorithm (SINS) performs well in cases of coning rotational motion. However, this method does ...

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In a recent study published in the Proceedings of the National Academy of Sciences, researchers from the United States of America developed and validated "TimeMachine," an algorithm that predicts the ...

ABC/2 is still widely accepted for volume estimations in spontaneous intracerebral hemorrhage (ICH) despite known limitations, which potentially accounts for controversial outcome-study results. The ...