Feedforward layered perceptron neural networks seek to capture a system mapping inferred by training data. A properly trained neural network is not only capable of mimicking the process responsible for generating the training data, but the inverse process as well. Neural network inversion procedures seek to find one or more input values that produce a desired output response for a fixed set of synaptic weights. There are many methods for performing neural network inversion. Multi-element evolutionary inversion procedures are capable of finding numerous inversion points simultaneously. Constrained neural network inversion requires that the inversion solution belong to one or more specified constraint sets. In many cases, iterating between the neural network inversion solution and the constraint set can successfully solve constrained inversion problems. This paper surveys existing methodologies for neural network inversion, which is illustrated by its use as a tool in query-based learning, sonar performance analysis, power system security assessment, control, and generation of codebook vectors.
A 420‐kHz, dual‐beam SONAR system, deployed on a remotely operated vehicle (ROV), was used to examine the fine structure of sound‐scattering layers (SSLs) in Puget Sound and the Arctic Ocean. The Puget Sound SSL, initially detected with a shipboard, 200‐kHz SONAR system, was correlated with a high biomass of sound scatterers in the size range of macrozooplankton and micronekton. Its vertical position appeared unrelated to profiles of temperature, salinity, or chlorophyll fluorescence. The Arctic Ocean SSL was composed of similar‐sized sound scatterers, although its volume backscattering intensity was 10–100 times lower than that observed for the Puget Sound SSL. The vertical position of the Arctic SSL was closely associated with the thermocline separating Arctic Water from North Atlantic Water.
The fine‐scale, horizontal variability of water‐column volume backscattering was examined at both study sites. The highest variability observed was associated with the Puget Sound SSL where the mean intensity of volume backscattering was also the highest. These findings are consistent with the common observation that, whatever methods are used to measure zooplankton and micronekton abundance, sampling variance nearly always increases with the mean.
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