Short Term Memory Quantifications in Input-Driven Linear Dynamical Systems
نویسندگان
چکیده
We investigate the relation between two quantitative measures characterizing short term memory in input driven dynamical systems, namely the short term memory capacity (MC) [2] and the Fisher memory curve (FMC) [1]. We show that under some assumptions, the two quantities can be interpreted as squared ‘Mahalanobis’ norms of images of the input vector under the system’s dynamics and that even though MC and FMC map the memory structure of the system from two quite different perspectives, they can be linked by a close relation.
منابع مشابه
Short term memory in input-driven linear dynamical systems
We investigate the relation between two quantitative measures characterizing short term memory in input driven dynamical systems, namely the short term memory capacity (MC) [3] and the Fisher memory curve (FMC) [2]. We show that even though MC and FMC map the memory structure of the system under investigation from two quite different perspectives, for linear input driven dynamical systems they ...
متن کاملMemory traces in dynamical systems.
To perform nontrivial, real-time computations on a sensory input stream, biological systems must retain a short-term memory trace of their recent inputs. It has been proposed that generic high-dimensional dynamical systems could retain a memory trace for past inputs in their current state. This raises important questions about the fundamental limits of such memory traces and the properties requ...
متن کاملCONTROL OF CHAOS IN A DRIVEN NON LINEAR DYNAMICAL SYSTEM
We present a numerical study of a one-dimensional version of the Burridge-Knopoff model [16] of N-site chain of spring-blocks with stick-slip dynamics. Our numerical analysis and computer simulations lead to a set of different results corresponding to different boundary conditions. It is shown that we can convert a chaotic behaviour system to a highly ordered and periodic behaviour by making on...
متن کاملThe Role of dopamine in the Maintenance of Working Memory in prefrontal Cortex Neurons: Input-Driven versus Internally-Driven Networks
How do organisms select and organize relevant sensory input in working memory (WM) in order to deal with constantly changing environmental cues? Once information has been stored in WM, how is it protected from and altered by the continuous stream of sensory input and internally generated planning? The present study proposes a novel role for dopamine (DA) in the maintenance of WM in the prefront...
متن کاملData-Driven Forecasting of High-Dimensional Chaotic Systems with Long-Short Term Memory Networks
We introduce a data-driven forecasting method for high dimensional, chaotic systems using Long-Short Term Memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high dimensional dynamical systems in their reduced order space and are shown to be an effective set of non-linear approximators of their attractor. We demonstrate the forecasting performance of ...
متن کامل