Abstract: In this paper we present a new computational primitive for convolution using coupled oscillator arrays. It is based on a Degree of Match (DOM) operation for pairs of vectors of analog ...

This latest installment in a long-term Frontline series is an intimate look at two American families, who work hard but struggle to make ends meet. By Margaret Lyons The Frontline documentary “Two ...

Deep convolutional neural networks (DCNNs) have been a game-changer for several computer vision tasks. These include object identification, object recognition, image segmentation, and edge detection.

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You have been given a sorted(in ascending order) integer array/list(ARR) of size N and an element X. Write a function to search this element in the given input array/list using 'Binary Search'. Return ...

Uses Toeplitz convolutional matrix multiplication to perform sparse convolution. This allows for extremely fast convolution when: The kernel is small (<= 100x100) The input array is sparse (<= 1% ...

NumPy is known for being fast, but could it go even faster? Here’s how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users a wickedly fast library for working with data in ...