Distributed hydrological models combine observations and knowledge about a hydrological system to make spatial predictions of hydrological attributes. These models require methods to assess their performance at spatial prediction. The current practice for assessment is simplistic. For qualitative assessment, simulated spatial patterns are compared visually against an observed pattern to assess ...

z In this paper, the one-dimensional principal component lter banks (PCFB's) derived in 17] are generalized to higher dimensions. As presented in 17], PCFB's minimize the mean-squared error (MSE) when only Q out of P subbands are retained. Previously, 2D PCFB's were proposed in 16]. The work in 16] was limited to 2D signals and separable resampling operators. The formulation presented here is g...

In this correspondence, a new time delay estimation procedure is proposed using the multiresolution analysis framework through a discrete wavelet transform (DWT). Once the signals are decomposed, the time delays are estimated iteratively in each sub-band using two different adaptation mechanisms that minimize the mean squared error (MSE) between the reference and primary signals in the correspo...

We consider monitoring the quality of compressed video transmitted over a packet network from the perspective of a network service provider. We estimate the Mean-Squared Error (MSE) caused by packet loss by examining only the received video bitstream. We describe our FullParse method, which extracts sequence-specific information including spatio-temporal activity and the effects of error propag...

Mean squared error (MSE) has been the most widely used tool to solve the linear filter estimation or system identification problem. However, MSE gives biased results when the input signals are noisy. This paper presents a novel stochastic gradient algorithm based on the recently proposed error whitening criterion (EWC) to tackle the problem of linear filter estimation in the presence of additiv...

Motivated by the need for distributed learning and optimization algorithms with low communication cost, we study communication efficient algorithms for distributed mean estimation. Unlike previous works, we make no probabilistic assumptions on the data. We first show that for d dimensional data with n clients, a naive stochastic rounding approach yields a mean squared error (MSE) of ⇥(d/n) and ...

Chronic diseases, such as coronary artery disease and diabetes, are caused by inadequate physical activity the leading cause of increasing mortality morbidity rates. Direct calorimetry calorie production indirect energy expenditure (EE) has been regarded best method for estimating EE. However, this is inconvenient, owing to use an oxygen respiration measurement mask. In study, we propose a mode...

It is well-known that the mean squared error (MSE) is an inappropriate measure for the difference between two images in many applications. For one such an application, edge-preserving smoothing, an alternative was developed which takes both goals into account: the preservation or sharpening of edges and the smoothing of regions. In this paper, tests on human subjects are reported which con rm t...