The authors used a Bayesian modeling framework to fit behavior and serotonin neuron activity to reward history across multiple timescales. A key goal was to distinguish value coding from other ...

THIS book is based upon a course of lectures given by the author at Cambridge during the Lent term of 1932. The introduction contains a condensed but useful account of Lebesgue integration, leading to ...

Abstract: Many real-world time series, such as electricity demand data, biomedical signals, and mechanical vibration signals, exhibit complex trends, encompass multiple seasonal (or periodic) ...

Abstract: In recent years, sparse unmixing (SU) has garnered significant attention in hyperspectral images (HSI) because it does not require endmember estimation, relying instead on prior spectral ...