TI's TMS320F28P550SJ MCU with an integrated neural processing unit is designed to run CNN models to help reduce latency and ...

These applications typically involve the exchange of small information blocks. Convolutional codes (CC) exhibit near-optimal performance when encoding short blocks. To enable packet-based ...

Abstract: We consider the problem of estimating the parameters of a convolutional encoder from noisy data observations, i.e. when encoded bits are received with errors. Reverse engineering of a ...

In this beginner’s guide, we dive into the different techniques for encoding categorical data, supported by visuals and practical code examples. Categorical data refers to variables that contain ...

QTS2D is a Python library for encoding time series data into image representations using quantum computing principles. These image-based representations can then be used as input for various machine ...

Official implementation of the paper "Feature Visualization in 3D Convolutional Neural Networks", which can disentangle texture and motion preferences of a target 3D conv kernel with a data-driven ...