The classification of remotely sensed multi-spectral data using classical statistical methods has been worked on for several decades. There have been many new developments in neural network (NN) research, and many new...
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The classification of remotely sensed multi-spectral data using classical statistical methods has been worked on for several decades. There have been many new developments in neural network (NN) research, and many new applications have been studied. It is well known that NN approaches have the ability to classify without assuming a distribution. The authors previously proposed an NN model to combine the spectral and spatial information of LANDSAT TM images. In this paper, the authors apply the NN approach with a normalization method to classify multi-temporal LANDSAT TM images in order to investigate the robustness of their approach. From the authors' experiments, they confirm that their approach is more effective for the classification of multi-temporal data than the original NN approach and maximum likelihood approach.
There have been many new developments in interactive analysis for multi-spectral images in the research of remote sensing. In general, the methods used are linear transformations such as principal component analysis. ...
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There have been many new developments in interactive analysis for multi-spectral images in the research of remote sensing. In general, the methods used are linear transformations such as principal component analysis. In this paper, the authors present a new interactive method for classifying multi-spectral images using a Hilbert curve which is a one-to-one mapping and preserves the neighborhood as much as possible. This method is based on a hierarchical histogram expression with different resolutions for the mapped one-dimensional data. The classification on this expression can be performed easily instead of using N-dimensional data directly. In order to realize the real time response from the system, the authors make use of data tables storing the addresses and the occurrences of data, etc. Here the address is defined by using the coordinates in N-dimensional space, and is made use of dealing with a part of mapping which can not preserve the neighborhood. In the experiments using LANDSAT image data, it is confirmed that the user can get the real time response from the system after once making the data tables.
This paper studies a mathematical model of general boundary input systems using the notion of fractional power of positive operators, and various properties of such systems are presented in the framework of semigroup ...
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This paper studies a mathematical model of general boundary input systems using the notion of fractional power of positive operators, and various properties of such systems are presented in the framework of semigroup approach. In particular, it is shown that every general boundary input system can be transformed into an equivalent distributed input system, and it is indicated that the equivalent system may be used to obtain various characterizations of the original general boundary input system.< >
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