Hilbert Transformation Impulse Response

Nonlinear impulse response functions

The standard linear technique of impulse response function analysis is extended to the nonlinear case by de"ning a generalized impulse response function. Measures of persistence and asymmetry in response are constructed for a wide class of time series. ( 2000 Elsevier Science B.V. All rights reserved. JEL classixcation: C22; C51; C52; E32

Which Impulse Response Function?

This paper compares standard and local projection techniques in the production of impulse response functions both theoretically and empirically. Through careful selection of a structural decomposition, the comparison continues to an application of US data to the textbook ISLM model. It is argued that local projection techniques offer a remedy to the bias of the conventional method especially at...

Finite Impulse Response Neural Networks

A neural network architecture, which models synapses as Finite Impulse Response (FIR) linear lters, is discussed for use in time series prediction. Analysis and methodology are detailed in the context of the Santa Fe Institute Time Series Prediction Competition. Results of the competition show that the FIR network performed remarkably well on a chaotic laser intensity time series.

Finite Impulse Response ( FIR ) Filters

Parallelizing Infinite Impulse Response Filters

In this paper, we present a parallel algorithm for edge detection based on Infinite Impulse Response filter (IIR filter). In particular, the Infinite size Symmetric Exponential Filter (ISEF) that is an optimal IIR filter and computationally efficient smoothing filter is studied. The proposed algorithm exploits efficiently all aspects of potential parallelism (spatial parallelism, temporal paral...