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Denoising without access to clean data using a partitioned autoencoder
Training a denoising autoencoder neural network requires access to truly clean data, a requirement which is often impractical. To remedy this, we introduce a method to train an... -
Quaternion one-dimensional offset linear canonical transform
The quaternion one-dimensional offset linear canonical transform (1D-QOLCT) is a novel integral transform that is embodiment of several well known signal processing tools. -
Advection of a square wave and a Gaussian function
The dataset used in this paper is a collection of solutions for advection of a square wave and a Gaussian function on a structured grid. -
Blind Hierarchical Deconvolution
The dataset used in the paper is a blind hierarchical deconvolution problem, where the goal is to deconvolve a signal from its noisy measurements. The dataset consists of four... -
A Deep Neural Network Based Reverse Radio Spectrogram Search Algorithm
Modern radio astronomy instruments generate vast amounts of data, and the increasingly challenging radio frequency interference (RFI) environment necessitates ever-more... -
Signal-adapted tight frames on graphs
Signal-adapted tight frames on graphs -
Diffusion-based Conditional ECG Generation with Structured State Space Models
Synthetic data generation is a promising solution to address privacy issues with the distribution of sensitive health data. Recently, diffusion models have set new standards for... -
Smooth signals dataset
Real-valued multi-dimensional time series data -
Sine waves dataset
Real-valued multi-dimensional time series data
