Related Experiment Video
Updated: Sep 10, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
Published on: August 16, 2017
Diversity and similarity of information transfers and flows in continuous-time stochastic systems
1Institute of Physics, Saratov State University, 155 Moskovskaya Street, Saratov 410012, Russia.
Abstract:
The framework of dynamical causal effects (DCEs) is applied to produce a logical sequence of a dozen of informational causality quantifiers for stochastic dynamical systems with continuous time and state. As distinct from the previously considered case of Markov chains, along with the informational DCEs with finite response time, the corresponding DCE rates of the first and second orders are introduced. Among them, several "information transfers and flows" widely known and used in time series analysis are present, including transfer entropy, Ay-Polani information flow, and Liang-Kleeman information flow. Analytic relationships between the informational DCEs under study are obtained. Typical numerical values of these DCEs and quantitative relationships between them are found using an ensemble of pairs of coupled stochastic relaxation systems.
Related Concept Videos
Classification of Systems-II
BIBO stability of continuous and discrete -time systems
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
Basic Continuous Time Signals
The unit step function, denoted u(t), is zero for negative time values and one for positive time values, exhibiting a discontinuity at t=0. This function often represents abrupt changes, such as the step voltage introduced when turning a car's...
Steady Flow of a Fluid Stream
During this process, the momentum of the fluid within the control volume remains constant over the time interval dt. By applying the...
Feedback control systems
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
Sampling Continuous Time Signal
In the...

