Sentence examples for feedback rules from inspiring English sources

Table 1 Control feedback rules ("adjust" mode: A, D ; "calibrate" mode: B, C).

Methods have been developed to monitor a process in the presence of feedback rules (Singer and Ben Gal 2007), as well as using feedback rules to help detect, explain, and prevent tampering with the processes (Georgantzas and Katsamakas 2008).

The paper is structured around the primary methods for solving quadratic-linear economic stochastic control models, namely open loop, classical control, handcrafted feedback rules, optimal feedback, min max control, optimal feedback rules with parameter uncertainty and dual control.

Third, a learning algorithm is designed to regulate validation results to generate feedback rules – Productions to guide the architecture evolution.

Our comparisons focus on simple feedback rules versus rules which are optimal, given knowledge of the correct economic structure and the appropriate loss function for the policymaker.

Moreover, the dependence of the current values of the instruments on lagged values of both the instruments and the targets is a fundamental property of feedback rules known as causality (see Astrom and Wittenmark 1996), essentially ensuring that the policy rules take into account all the relevant information available regarding the state of the economy.

By considering a few additional nonlinear devices for thresholding and all-optical switching we then show how to construct a perceptron, including the perceptron feedback rule.

The paper explores the potential uses of parametric modeling to embed construction and structural design knowledge in the form of generative rules and feedback rule-checking functions.

In this article, for improving the maximum power and capacity of actuators for amplitude depreciation of negative velocity feedback strategy, we have proposed a new control strategy, called "Saturated Negative Velocity Feedback Rule (SNVF)".

We consider a broad class of linear dynamic stochastic rational-expectations models made of a finite number N of structural equations for N+1 endogenous variables and to be closed by one policy feedback rule.

We present nonlinear photonic circuit models for constructing programmable linear transformations and use these to realize a coherent perceptron, i.e., an all-optical linear classifier capable of learning the classification boundary iteratively from training data through a coherent feedback rule.