A General Close-loop Predictive Coding Framework for Auditory Working Memory
Auditory working memory is essential for various daily activities, such as language acquisition, conversation. It involves the temporary storage and manipulation of information that is no longer present in the environment. While extensively studied in neuroscience and cognitive science, research on its modeling within neural networks remains limited. To address this gap, we propose a general framework based on a close-loop predictive coding paradigm to perform short auditory signal memory tasks. The framework is evaluated on two widely used benchmark datasets for environmental sound and speech, demonstrating high semantic similarity across both datasets.
Code (0)
등록된 구현이 없습니다.
Tasks
Language AcquisitionSemantic SimilaritySemantic Textual SimilaritySimilar Papers 제목 키워드 기반
Predictive control for nonlinear stochastic systems: Closed-loop guarantees with unbounded noise
We present a stochastic model predictive control framework for nonlinear systems subject to unbounded process noise with closed-loop guarantees. First, we provide a conceptual shrinking-horizon framework that utilizes ge…
Computational EfficiencyFrictionModel Predictive ControlClosed-loop Data-Enabled Predictive Control and its equivalence with Closed-loop Subspace Predictive Control
Factors like improved data availability and increasing system complexity have sparked interest in data-driven predictive control (DDPC) methods like Data-enabled Predictive Control (DeePC). However, closed-loop identific…
Stability-informed Bayesian Optimization for MPC Cost Function Learning
Designing predictive controllers towards optimal closed-loop performance while maintaining safety and stability is challenging. This work explores closed-loop learning for predictive control parameters under imperfect in…
Bayesian Optimizationglobal-optimizationStochastic Model Predictive Control for Sub-Gaussian Noise
We propose a stochastic Model Predictive Control (MPC) framework that ensures closed-loop chance constraint satisfaction for linear systems with general sub-Gaussian process and measurement noise. By considering sub-Gaus…
modelModel Predictive ControlPredictive Coding: a Theoretical and Experimental Review
Predictive coding offers a potentially unifying account of cortical function -- postulating that the core function of the brain is to minimize prediction errors with respect to a generative model of the world. The theory…