This paper deals with the analysis of evolutionary design in different approximate circuit designs. The key character of these designs is to relax the functionality of the circuits to minimize energy consumption or area of the chip. Keywords—Approximate design, Cartesian genetic programming, gates scaling.

We consider L1-isotonic regression and L∞ isotonic and unimodal regression. For L1isotonic regression, we present a linear time algorithm when the number of outputs are bounded. We extend the algorithm to construct an approximate isotonic regression in linear time when the output range is bounded. We present linear time algorithms for L∞ isotonic and unimodal regression.

An online adaptive reinforcement learning-based solution is developed for the infinite-horizon optimal control problem for continuous-time uncertain nonlinear systems. A novel actor–critic–identifier (ACI) is proposed to approximate the Hamilton–Jacobi–Bellman equation using three neural network (NN) structures—actor and critic NNs approximate the optimal control and the optimal value function,...

The behavioral theory of dynamical system is used to address a deterministic system identification problem with a newly defined measure of misfit between data and linear time-invariant systems. An approximate model identification problem is formalized using this misfit criterium. In particular, Pareto optimal models are defined as feasible trade-offs between low complexity and low misfit models...

IT-enabled exchanges in electronic markets have significant implications for buyer-supplier relationships. Building on previous research that emphasizes the role of intangible assets in inter-organizational relationships, this study argues that buyers are less likely to use reverse auctions for supplier relationships involving a high degree of non-contractibility. The argument complements tradi...

In this paper we propose a novel algorithm that provides bounded approximate solutions for decentralised coordination problems. Our approach removes cycles in any general constraint network by eliminating dependencies between functions and variables which have the least impact on the solution quality. It uses the max-sum algorithm to optimally solve the resulting tree structured constraint netw...

An adaptive servomechanism is developed in the context of the problem of approximate or practical tracking (with prescribed asymptotic accuracy), by the system output, of any admissible reference signal (absolutely continuous and bounded with essentially bounded derivative) for every member of a class of controlled dynamical systems modelled by functional differential equations.