Learning Overcomplete Representations Lewicki, Michael S.; Sejnowski, Terrence J.
Neural computation,
02/2000, Letnik:
12, Številka:
2
Journal Article
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In an overcomplete basis, the number of basis vectors is greater than the dimensionality of the input, and the representation of an input is not a unique combination of basis vectors. Overcomplete ...representations have been advocated because they have greater robustness in the presence of noise, can be sparser, and can have greater flexibility in matching structure in the data. Overcomplete codes have also been proposed as a model of some of the response properties of neurons in primary visual cortex. Previous work has focused on finding the best representation of a signal using a fixed overcomplete basis (or dictionary). We present an algorithm for learning an overcomplete basis by viewing it as probabilistic model of the observed data. We show that overcomplete bases can yield a better approximation of the underlying statistical distribution of the data and can thus lead to greater coding efficiency. This can be viewed as a generalization of the technique of independent component analysis and provides a method for Bayesian reconstruction of signals in the presence of noise and for blind source separation when there are more sources than mixtures.
Quantifying suspended sediment loads is important for managing the world's estuaries in the context of navigation, pollutant transport, wetland restoration, and coastal erosion. To address these ...needs, a comprehensive analysis was completed on sediment supply to San Francisco Bay from fluvial sources. Suspended sediment, optical backscatter, velocity data near the head of the estuary, and discharge data obtained from the output of a water balance model were used to generate continuous suspended sediment concentration records and compute loads to the Bay from the large Central Valley watershed. Sediment loads from small tributary watersheds around the Bay were determined using 235 station-years of suspended sediment data from 38 watershed locations, regression analysis, and simple modeling. Over 16years, net annual suspended sediment load to the head of the estuary from its 154,000km2 Central Valley watershed varied from 0.13 to 2.58 (mean=0.89)millionmetrict of suspended sediment, or an average yield of 11metric t/km2/yr. Small tributaries, totaling 8145km2, in the nine-county Bay Area discharged between 0.081 and 4.27 (mean=1.39)millionmetrict with a mean yield of 212metrict/km2/yr. The results indicate that the hundreds of urbanized and tectonically active tributaries adjacent to the Bay, which together account for just 5% of the total watershed area draining to the Bay and provide just 7% of the annual average fluvial flow, supply 61% of the suspended sediment. The small tributary loads are more variable (53-fold between years compared to 21-fold for the inland Central Valley rivers) and dominated fluvial sediment supply to the Bay during 10 out of 16yr. If San Francisco Bay is typical of other estuaries in active tectonic or climatically variable coastal regimes, managers responsible for water quality, dredging and reusing sediment accumulating in shipping channels, or restoring wetlands in the world's estuaries may need to more carefully account for proximal small urbanized watersheds that may dominate sediment supply.
•Fluvial suspended sediment loads to the tidal zone of San Francisco Bay.•Suspended sediment loads in Central Valley Rivers vary 21-fold between years.•Suspended sediment loads in small tributaries vary 53-fold between years.•Step-changes in sediment loads between wet and dry periods were observed.•Small tributaries covering 5% of the watershed area, supply 61% of the sediment.
Rothia aeria is a gram-positive, pleomorphic bacteria forming part of human oral microflora usually only causing periodontal and dental infections. We describe the case of a 68-year-old ...immunocompetent male with lumbar vertebral discitis/osteomyelitis caused by R. aeria. A review of the literature demonstrated seventeen cases of non-dental R. aeria infection of which only six were in immunocompetent individuals. This is the first reported case of R. aeria vertebral discitis/osteomyelitis.
We study domain walls interpolating between the physical electroweak vacuum and the global minimum of the Standard Model scalar potential appearing at very high field strengths. Such domain walls ...could be created in the early Universe under the assumption of validity of the Standard Model up to very high energy scales. The creation of the network of domain walls which ends up in the electroweak vacuum percolating through the Universe is not as difficult to obtain as one may expect, although it requires certain tuning of initial conditions. Our numerical simulations confirm that such domain walls would swiftly decay. Moreover we have found that for the standard cosmology the energy density of gravitational waves emitted from domain walls is too small to be observed in present and planned detectors.
The detection of neural spike activity is a technical challenge that is a prerequisite for studying many types of brain function. Measuring the activity of individual neurons accurately can be ...difficult due to large amounts of background noise and the difficulty in distinguishing the action potentials of one neuron from those of others in the local area. This article reviews algorithms and methods for detecting and classifying action potentials, a problem commonly referred to as spike sorting. The article first discusses the challenges of measuring neural activity and the basic issues of signal detection and classification. It reviews and illustrates algorithms and techniques that have been applied to many of the problems in spike sorting and discusses the advantages and limitations of each and the applicability of these methods for different types of experimental demands. The article is written both for the physiologist wanting to use simple methods that will improve experimental yield and minimize the selection biases of traditional techniques and for those who want to apply or extend more sophisticated algorithms to meet new experimental challenges.
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