This paper proposes a model of endogenous fluctuations in investment. A monopolistic producer has an incentive to invest when the aggregate demand is high. This causes a propagation of investment across sectors. When the investment follows an (S,s) policy, the propagation size can exhibit a significant fluctuation. We characterize the probability distribution of the propagation size, and show t...

We focus on the channel estimation and the decoding of orthogonal frequency-division multiplexing (OFDM) signals in networking scenarios with multipath propagation and strong cochannel interference (CCI). The receiver views the CCI contained in the subchannel signal observations as additional independent Gaussian noise terms with varying variance from subchannel to subchannel as a consequence o...

This paper adopts the stochastic simulation method that pertains to geostatistics, on the basis of simulated DEM realizations with spatial autocorrelation errors, to explore the error propagation mechanism of DEM-DON-DLG under the digital photogrammetry environment. It follows this procedure: first, produce 100 error-disturbed DEMs by means of sequential Gaussian simulation; next, attain 100 re...

n this work we examine blind adaptive and iterative decision feedback (DF) receivers for direct sequence code division multiple access (DS-CDMA) systems in frequency selective channels. Code-constrained minimum variance (CMV) and constant modulus (CCM) design criteria for DF receivers based on constrained optimization techniques are investigated for scenarios subject to multipath. Computational...

Abstract The barrier effect of the Maritime Continent (MC) in stalling or modifying propagation characteristics MJO is widely accepted. strong diurnal cycle convection over MC believed to play a dominant role this regard. This hypothesis studied here, with help coarse-resolution atmospheric general circulation model (AGCM). dry dynamical core AGCM coupled multicloud parameterization piggybacked...

Multi-atlas segmentation methods are among the most accurate approaches for the automatic labeling of magnetic resonance (MR) brain images. The individual segmentations obtained through multi-atlas propagation can be combined using an unweighted or locally weighted fusion strategy. Label overlaps can be further improved by refining the label sets based on the image intensities using the Expecta...

We introduce $k$-variance, a generalization of variance built on the machinery random bipartite matchings. $K$-variance measures expected cost matching two sets $k$ samples from distribution to each other, capturing local rather than global information about measure as increases; it is easily approximated stochastically using sampling and linear programming. In addition defining $k$-variance pr...