共查询到20条相似文献，搜索用时 739 毫秒
1.
Estuaries exhibit a large range in their responses to nitrogen loadings determined in part by characteristics of the driver, such as magnitude and frequency, but also by such intrinsic characteristics as physical/chemical factors (e.g., depth, volume, hypsometry, salinity, turbidity) and biological factors (e.g., nature of ecological communities, trophic interactions). To address the richness of estuarine response to driver variables, the aim ultimately is to establish a simple estuarine classification scheme, beginning with a river-dominated subset of estuarine systems and focusing on the role of water residence time in the estuary. Residence time (or flushing time) is related to other drivers (streamflow, nutrient, and sediment loads) and drives much of the biological response of estuaries because of flushing effects on plankton, temperature, nutrients, and light. Toward this goal, nutrient–phytoplankton–zooplankton (NPZ) models have been used to examine a range of subjects including effects of nutrient limitation and zooplankton predation on phytoplankton dynamics and fish predation. This class of model can admit a wide range of behavior, including multiple steady-states and oscillatory behavior. The NPZ equations include terms for nutrient recycling, phytoplankton settling, benthic regeneration, and zooplankton mortality. Analysis of the equations suggests that both the nature of nitrogen loading (i.e., whether it is correlated with discharge or independent of it) and residence time are critical in determining the steady-state response of the system. 相似文献
2.
It has long been known that the statistical properties of acoustic echoes from individual fish can have non-Rayleigh characteristics. The statistical properties of echoes from zooplankton are generally less understood. In this study, echoes from individual fish and zooplankton from a series of laboratory measurements from the past decade are investigated. In the experiments, acoustic echoes from various individual organisms were measured over a wide range of frequencies and orientations, typically in 1/spl deg/-3/spl deg/ increments. In the analysis in this paper, the echoes from most of those measurements are grouped according to ranges of orientation, which correspond to typical orientation distributions of these organisms in the natural ocean environment. This grouping provides a distribution of echo values for each range of orientation. This approach, in essence, emulates a field experiment whereby distributions of echoes would be recorded for different distributions of orientations of the organisms. For both the fish and zooplankton data, there are conditions under which the echoes are strongly non-Rayleigh distributed. In some cases, the distribution is quantitatively connected to the physics of the scattering process while, in other cases, the connection is described qualitatively. Exploitation of the animal-specific statistics for classification purposes is suggested. 相似文献
3.
Shape classification of the 40-Hz waveforms obtained by the recently launched AltiKa satellite has been attempted in the paper. Since retracking algorithms suitable for altimeter return echoes based on Brown model are not applicable for the echoes from coastal ocean, specific algorithms are to be devised for such echoes. In the coastal ocean, waveforms display a wide variety of shapes due to varying coastline geometry, and topography. Hence, a proper classification strategy is required for classifying the waveforms into various categories so that suitable retracker could be applied to each category for retrieving the oceanic parameters. The algorithm consists of three steps: feature selection, linear discriminant analysis, and Bayesian classifier. The classification algorithm has been applied to the waveforms in the close proximity of Gujarat coast. Independent validation has been done near the eastern coast of India. Confusion matrices obtained for both the coasts are quite encouraging. Individual examples of classification have been provided for the purpose of illustration. 相似文献
4.
Traditionally, matched-field processing (MFP) has been used to localize low-frequency sources (e.g., <300 Hz) from their acoustic signals received on long vertical arrays. However, some sources emit acoustic signals of much higher frequency. Applying MFP to signals in the mid-frequency range (e.g., 1-4 kHz) is a very challenging problem because MFP's sensitivity to environmental parameter mismatch becomes more severe with increasing frequency. Robust MFP techniques are required to process signals in the mid-frequency range. As a practical issue, short vertical arrays are more convenient to work with than are long vertical arrays; they are easier to deploy and are less prone to large amounts of deformation. However, short vertical arrays undersample the water column, which can result in severely degraded MFP performance. In this paper, we present experimental data results for this nonconventional paradigm. Using the environmentally robust broad-band L/sub /spl infin//-norm estimator, MFP results are given using shallow-water experimental data. This data consisted of broad-band signals in the 3-4-kHz band collected on an eight-element 2.13-m vertical array. These results serve to demonstrate that good localization performance can be attained for this difficult problem. Guidelines on the appropriate use of ray and normal-mode propagation models are also presented. 相似文献
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Acoustic echoes obtained during high-resolution shallow marine seismic surveys contain information about the statistical nature of the sedimentary bottom and its spatial variability. Use of a broad-band seismic source and an appropriately chosen data acquisition window makes the acoustic responses particularly amenable to quantitive analysis. The work reported utilizes experimental frequency-domain spatial coherence functions of along-track acoustic echoes as empirical metrics of bottom character, and by virtue of their correlation with known sediment types, as objective bases for remote sediment classification. Theoretical relationships between parameters describing sediment surface topographies and echo coherence are derived for the case of dominant water-sediment interface acoustic scattering. The diverse experimental data base was acquired from the Grand Banks of Newfoundland using a 1- to 10-kHz Huntec DTS system. Bottom photographs, cores, and grab samples combined with expert geological synthesis provide qualitative and quantitative control. 相似文献
7.
Warren J.D. Stanton T.K. McGehee D.E. Dezhang Chu 《Oceanic Engineering, IEEE Journal of》2002,27(1):130-138
It is well known that the behavior of zooplankton and, in particular, their orientation distribution dramatically affects the level of backscattered acoustic energy. As a result, interpretation of acoustic survey data in the ocean is subject to error. In order to quantify these effects, laboratory data from two important classes of animals were collected. The data involved broad-band (350-650 kHz) acoustic signals insonifying individual animals whose orientation was varied over the range 0°-360° in 1° increments. The animals were from two major anatomical groups: fluid-like (decapod shrimp; Palaemonetes vulgaris) and elastic-shelled (periwinkles; Littorina littorea). The data were analyzed both in the time domain (with pulse compression processing) and the frequency domain. Averages of the laboratory data over different orientation distributions illustrate the variability in average target strength that can be expected in the ocean environment. The average target strength of the shrimp varied by 3 dB when averaged over orientation distributions centered around broadside and end-on incidence. In addition, size estimates from pulse compression processing of the broad-band echoes were made for various orientation distributions for both the shrimp and periwinkles. These results show the necessity of animal orientation information for the proper interpretation of acoustic backscatter data 相似文献
8.
In ocean surveillance, a number of different types of transient signals are observed. These sonar signals are waveforms in one dimension (1-D). The hidden Markov model (HMM) is well suited to classification of 1-D signals such as speech. In HMM methodology, the signal is divided into a sequence of frames, and each frame is represented by a feature vector. This sequence of feature vectors is then modeled by one HMM. Thus, the HMM methodology is highly suitable for classifying the patterns that are made of concatenated sequences of micro patterns. The sonar transient signals often display an evolutionary pattern over the time scale. Following this intuition, the application of HMM's to sonar transient classification is proposed and discussed in this paper. Toward this goal, three different feature vectors based on an autoregressive (AR) model, Fourier power spectra, and wavelet transforms are considered in our work. In our implementation, one HMM is developed for each class of signals. During testing, the signal to be recognized is matched against all models. The best matched model identifies the signal class. The neural net (NN) classifier has been successfully used previously for sonar transient classification. The same set of features as mentioned above is then used with a multilayer perceptron NN classifier. Some experimental results using “DARPA standard data set I” with HMM and MLP-NN classification schemes are presented. A combined NN/HMM classifier is proposed, and its performance is evaluated with respect to individual classifiers 相似文献
9.
《Oceanic Engineering, IEEE Journal of》2005,30(3):588-600
This paper describes a novel framework for classifying underwater transient signals recorded by passive sonar. The proposed approach involves two key ideas. Firstly, a feature-selection algorithm is used to identify those acoustic features that optimally model each class of transient sound. Secondly, features that are perceptually motivated are proposed, i.e., they encode information that human listeners are likely to use in transient classification tasks. Three perceptual features are proposed, which encode timbre, the physical material of the sound source, and the temporal context (pattern) in which the transient occurred. The authors show how these features, which are computed over different temporal windows, can be combined to make classification decisions. The performance of the proposed classifier is evaluated on a corpus of transient signals extracted from passive sonar recordings. Specifically, the performance of the perceptual features is compared with spectral features and with those that encode statistics of time, frequency, and power. The present results show that the perceptual features provide valuable cues to the class of a transient. However, the best performing classifier was obtained by selecting a subset of perceptual, spectral, and statistical features in a class-dependent manner. 相似文献
10.
In this paper, we use matched-field inversion methods to estimate the geoacoustic parameters for three synthetic test cases from the Geoacoustic Inversion Techniques Workshop held in May 2001 in Gulfport, MS. The objective of this work is to use a sparse acoustic data set to obtain estimates of the parameters as well as an indication of their uncertainties. The unknown parameters include the geoacoustic properties of the sea bed (i.e., number of layers, layer thickness, density, compressional speed, and attenuation) and the bathymetry for simplified range-dependent acoustic environments. The acoustic data used to solve the problems are restricted to five frequencies for a single vertical line array of receivers located at one range from the source. Matched-field inversion using simplex simulated annealing optimization is initially used to find a maximum-likelihood (ML) estimate. However, the ML estimate provides no information on the uncertainties or covariance associated with the model parameters. To estimate uncertainties, a Bayesian formulation of matched-field inversion is used to generate posterior probability density distributions for the parameters. The mean, covariance, and marginal distributions are determined using a Gibbs importance sampler based on the cascaded Metropolis algorithm. In most cases, excellent results were obtained for relatively sensitive parameters such as wave speed, layer thickness, and water depth. The variance of the estimates increase for relatively insensitive parameters such as density and wave attenuation, especially when noise is added to the data. 相似文献
11.
Subbottom acoustic profiler provides acoustic imaging of the subbottom structure constituting the upper sediment layers of the seabed, which is essential for geological and offshore geo-engineering studies. Delineation of the subbottom structure from a noisy acoustic data and classification of the sediment strata is a challenging task with the conventional signal processing techniques. Image processing techniques utilise the spatial variability of the image characteristics, known for their potential in medical imaging and pattern recognition applications. In the present study, they are found to be good in demarcating the boundaries of the sediment layers associated with weak acoustic reflectivity, masked by noisy background. The study deals with application of image processing techniques, like segmentation in identification of subbottom features and extraction of textural feature vectors using grey level co-occurrence matrix statistics. And also attempted classification using Self Organised Map, an unsupervised neural network model utilising these feature vectors. The methodology was successfully demonstrated in demarcating the different sediment layers from the subbottom images and established the sediments constituting the inferred four subsurface sediment layers differ from each other. The network model was also tested for its consistency, with repeated runs of different configuration of the network. Also the ability of simulated network was tested using a few untrained test images representing the similar environment and the classification results show a good agreement with the anticipated. 相似文献
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The unique environment of the abyssal plains allows many simplifying assumptions, facilitating the acoustic classification of an animal into one of two groups. The most important assumptions are based on low population densities and available target strength histograms and swim rate histograms. The likelihood ratio is formed from this information and accepted signal processing theory. The likelihood function, a three-dimensional integral, is analytically simplified to one dimension and then solved numerically. A simulation based on this solution and measured data demonstrates that classification using the likelihood ratio approach is accurate, e.g. the sensitivity is ⩾0.8. Although the measured data come from two abyssopelagic genera, the methods presented are more generally applicable. Simulations based on hypothetical animal populations show that under certain conditions, a near perfect classification can be made, e.g. sensitivity and specificity greater than 0.969 相似文献
14.
基于自适应增强算法（AdaBoost）结合极限学习机（ELM）,通过迭代、调整、优化ELM分类器之间的权值,从而构建了具有强鲁棒性、高精度的ELM-AdaBoost强分类器,增强了现有的ELM分类器的稳定性。以珠江口海区侧扫声呐图像为实验数据,对礁石、砂、泥3类典型底质进行分类识别,该方法的平均分类精度超过90%,优于单一ELM分类器的平均分类精度85.95%,也优于LVQ、BP等传统分类器,且在分类所耗时间上也远少于传统分类器。实验结果表明,本文构建的ELM-AdaBoost方法可有效应用于海底声学底质分类,可满足实时底质分类的需求。 相似文献
15.
De Yao Azimi-Sadjadi M.R. Jamshidi A.A. Dobeck G.J. 《Oceanic Engineering, IEEE Journal of》2002,27(3):619-627
The problem of classifying underwater targets is addressed in this paper. The proposed classification system consists of several subsystems including preprocessing, subband decomposition using wavelet packets, linear predictive coding, feature selection and neural network classifier. A multi-aspect fusion system is introduced to further improve the classification accuracy. The classification performance of the overall system is demonstrated and benchmarked on two different acoustic backscattered data sets with 40- and 80-kHz bandwidth. A comprehensive study is then carried out to compare the classification performance using these data sets in terms of the receiver operating curves, error locations, and generalization and robustness on a large set of noisy data. Additionally, the importance of different frequency bands for the wideband 80-kHz data is also investigated. For the wideband data, a subband fusion mechanism is introduced which offers very promising results. 相似文献
16.
Wendy Gentleman Andrew Leising Bruce Frost Suzanne Strom James Murray 《Deep Sea Research Part II: Topical Studies in Oceanography》2003,50(22-26):2847
Modelers often need to quantify the rates at which zooplankton consume a variety of species, size classes and trophic types. Implicit in the equations used to describe the multiple resource functional response (i.e. how nutritional intake varies with resource densities) are assumptions that are not often stated, let alone tested. This is problematic because models are sensitive to the details of these formulations. Here, we enable modelers to make more informed decisions by providing them with a new framework for considering zooplankton feeding on multiple resources. We define a new classification of multiple resource responses that is based on preference, selection and switching, and we develop a set of mathematical diagnostics that elucidate model assumptions. We use these tools to evaluate the assumptions and biological dynamics inherent in published multiple resource responses. These models are shown to simulate different resource preferences, implied single resource responses, changes in intake with changing resource densities, nutritional benefits of generalism, and nutritional costs of selection. Certain formulations are further shown to exhibit anomalous dynamics such as negative switching and sub-optimal feeding. Such varied responses can have vastly different ecological consequences for both zooplankton and their resources; inappropriate choices may incorrectly quantify biologically-mediated fluxes and predict spurious dynamics. We discuss how our classes and diagnostics can help constrain parameters, interpret behaviors, and identify limitations to a formulation's applicability for both regional (e.g. High-Nitrate-Low-Chlorophyll regions comprising large areas of the Pacific) and large-scale applications (e.g. global biogeochemical or climate change models). Strategies for assessing uncertainty and for using the mathematics to guide future experimental investigations are also discussed. 相似文献
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JEFFREY L. ANDERSON 《地球，A辑:动力气象学与海洋学》2009,61(1):72-83
Ensemble filters are used in many data assimilation applications in geophysics. Basic implementations of ensemble filters are trivial but are susceptible to errors from many sources. Model error, sampling error and fundamental inconsistencies between the filter assumptions and reality combine to produce assimilations that are suboptimal or suffer from filter divergence. Several auxiliary algorithms have been developed to help filters tolerate these errors. For instance, covariance inflation combats the tendency of ensembles to have insufficient variance by increasing the variance during the assimilation. The amount of inflation is usually determined by trial and error. It is possible, however, to design Bayesian algorithms that determine the inflation adaptively. A spatially and temporally varying adaptive inflation algorithm is described. A normally distributed inflation random variable is associated with each element of the model state vector. Adaptive inflation is demonstrated in two low-order model experiments. In the first, the dominant error source is small ensemble sampling error. In the second, the model error is dominant. The adaptive inflation assimilations have better mean and variance estimates than other inflation methods. 相似文献
19.
The presently studied numerical model, e.g., composite roughness, is successful for the purpose of seafloor classification employing processed multibeam angular backscatter data from manganese-nodule-bearing locations of the Central Indian Ocean Basin. Hybrid artificial neural network (ANN) architecture, comprised of the self-organizing feature map and learning vector quantization (LVQ), has been implemented as an alternative technique for sea-floor roughness classification, giving comparative results with the aforesaid numerical model for processed multibeam angular backscatter data. However, the composite-roughness model approach is protracted due to the inherent need for processed data including system-gain corrections. In order to establish that tedious processing of raw backscatter values is unessential for efficient classification, hybrid ANN architecture has been attempted here due to its nonparametric approach. In this technical communication, successful employment of LVQ algorithm for unprocessed (raw) multibeam backscatter data indicates true real-time classification application. 相似文献
20.
A neural network based hybrid system for detection,characterization, and classification of short-duration oceanic signals 总被引：2，自引：0，他引：2
A comprehensive classifier system is presented for short-duration oceanic signals obtained from passive sonar, which exhibit variability in both temporal and spectral characteristics even in signals obtained from the same source. Wavelet-based feature extractors are shown to be superior to the more commonly used autoregressive coefficients and power spectral coefficients for describing these signals. A variety of static neural network classifiers are evaluated and are shown to compare favorably with traditional statistical techniques for signal classification. The focus is on those networks that are able to time-out irrelevant input features and are less susceptible to noisy inputs, and two new neural-network-based classifiers are introduced. Methods for combining the outputs of several classifiers to yield a more accurate labeling are proposed and evaluated. These methods lead to higher classification accuracy and provide a mechanism for recognizing deviant signals and false alarms. Performance results are given for signals in the DARPA standard data set I 相似文献