This paper examines the causal relationship between energy use and real GDP for the period 1967-2002 in Iran. The results of Phillips- Perron test indicate that the real GDP and the four categories of energy, i.e. coal, oil, gas, and hydroelectric energy are integrated of order one. Besides, the Johansen — Juselius maximum likelihood co- integration tests imply the existence of Granger causalit...

The Causally Dynamic Hybrid Bond Graph is extended to the case of modeswitching behaviour. Mode-switching ‘trees’ of switches and elements are historically used by bond graph practitioners to represent elements with piecewise-continuous functions. This case is defined as ‘parametric switching’ for the purposes of the hybrid bond graph, since the switching is internal to the element, as opposed ...

Recently, nonlinear vector autoregressive (NVAR) model based on Granger causality was proposed to infer nonlinear gene regulatory networks from time series gene expression data. Since NVAR requires a large number of parameters due to the basis expansion, the length of time series microarray data is insufficient for accurate parameter estimation and we need to limit the size of the gene set stro...

Feedforward control of sound and vibration using a neural network-based control system is considered, with the aim being to derive an architecture/algorithm combination which is capable of supplanting the commonly used finite impulse response filter/filtered-x least mean square (LMS) linear arrangement for certain nonlinear problems. An adaptive algorithm is derived which enables stable adaptat...

It is well-known that the solution of the classical linear wave equation with compactly supported initial condition and vanishing initial velocity is also compactly supported in a set depending on time : the support of the solution at time t is causally related to that of the initially given condition. Reed and Simon have shown that for a real-valued Klein-Gordon equation with (nonlinear) right...

We propose a general matrix-valued multiple kernel learning framework for highdimensional nonlinear multivariate regression problems. This framework allows a broad class of mixed norm regularizers, including those that induce sparsity, to be imposed on a dictionary of vector-valued Reproducing Kernel Hilbert Spaces. We develop a highly scalable and eigendecompositionfree algorithm that orchestr...

We propose a general matrix-valued multiple kernel learning framework for highdimensional nonlinear multivariate regression problems. This framework allows a broad class of mixed norm regularizers, including those that induce sparsity, to be imposed on a dictionary of vector-valued Reproducing Kernel Hilbert Spaces [19]. We develop a highly scalable and eigendecomposition-free Block coordinate ...

this study attempts to investigate the effect of oil returns and external debt on the government expenditure in syria over the period 1970-2010. the johansen cointegration test showed that oil returns and external debt have a positive and significant long run relationship with government expenditure. the granger causality test indicates unidirectional short-run causality relationships running f...

as a result of higher crude oil prices, in one hand, it is expected that alternative energy resources consumption is increased and consumers change their behavior to decline energy intensity too. on the other hand, more alternative energy consumption can leads to a decline of crude oil aggregate demand. therefore, existence of mutual causality between crude oil price and alternative energy cons...

Multi-resolution image analysis utilizes subsampled image representations for applications such as image coding, hierarchical image segmentation and fast image smoothing. An anti-aliasing filter may be used to insure that the sampled signals adequately represent the frequency components/features of the higher resolution signal. Sampling theories associated with linear anti-aliasing filtering ar...