Not everyone will write their own optimizing compiler from scratch, but those who do sometimes roll into it during the course ...

Understanding the benefits of matrix converters for EV chargers and a comparison of different matrix converter topologies.

Abstract: Matrix factorization is a fundamental characterization model in machine learning and is usually solved using mathematical decomposition reconstruction loss. However, matrix factorization is ...

Abstract: Matrix factorization is a central paradigm in matrix completion and collaborative filtering. Low-rank factorizations have been extremely successful in reconstructing and generalizing ...

Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

String manipulation is a core skill for every Python developer. Whether you’re working with CSV files, log entries, or text analytics, knowing how to split strings in Python makes your code cleaner ...

Multiplication in Python may seem simple at first—just use the * operator—but it actually covers far more than just numbers. You can use * to multiply integers and floats, repeat strings and lists, or ...

This is a translation of the MEMD (Multivariate Empirical Mode Decomposition) code from Matlab to Python. The Matlab code was developed by [1] and is freely available ...