drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

A method to simulate digital human running using an optimization-based approach is presented. The digital human is considered as a mechanical system that includes link lengths, mass moments of inertia, joint torques, and external forces. The problem is formulated as an optimization problem to determine the joint angle profiles. The kinematics analysis of the model is carried out using the Denav...

The article deals with the epistemological dimensions of the method of functional analysis of equivalence. This more general epistemological discussion enables the discovery of common heuristic grounds in the quantitative (explanation) and qualitative (understanding) methodologies in the social sciences . There are three main topics of interest . First, theoretical reasons for the formulation o...

This paper proposes a Lyapunov-based economic MPC scheme for nonlinear sytems with non-monotonic Lyapunov functions. Relaxed Lyapunov-based constraints are used in the MPC formulation to improve the economic performance. These constraints will enforce a Lyapunov decrease after every few steps. Recursive feasibility and asymptotical convergence to the steady state can be achieved using Lyapunov-...

A new multichannel filtered-x recursive least square algorithm for active noise control systems is proposed. It is shown that the use of the filtered-x structure, instead of the commonly used modified filtered-x structure lead to a more efficient implementation and similar convergence performance and stability. The paper is also focused on examining the benefits of auxiliary normal equations so...

in this paper, using generalized {polya} urn models we find the expected value of the size of a branch in recursive $k$-ary trees. we also find the expectation of the number of nodes of a given outdegree in a branch of such trees.

Many time series of practical interest are periodic and digital in nature. A simple state space formulation of a general digital periodic time series is constructed. This allows us to design and propose a simple partially recurrent back-propagation neural network with adaptive error thresh-olding suitable for prediction and parameter estimation of periodic time series sequences. Such an approac...

This paper proposes the use of constraint logic to perform model checking of imperative, infinite-state programs. We present a semantics-preserving translation from an imperative language with recursive procedures and heap-allocated mutable data structures into constraint logic. The constraint logic formulation provides a clean way to reason about the behavior and correctness of the original pr...

We use statistical detection theory in a continuous-time environment to provide a new perspective on calibrating a concern about robustness or an aversion to ambiguity. A decision maker repeatedly confronts uncertainty about state transition dynamics and a prior distribution over unobserved states or parameters. Two continuous-time formulations are counterparts of two discrete-time recursive sp...