Masked image modeling (MIM), a common selfsupervised learning (SSL) technique, has been extensively studied for remote sensing imageprocessing. Nevertheless, its effectiveness for hyperspectral imagery (HSI) remains ...
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Sequences with low/zero ambiguity zone (LAZ/ZAZ) properties are useful in modern communication and radar systems operating over mobile environments. This paper first presents a new family of ZAZ sequence sets motivate...
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A new deflected stochastic-gradient algorithm for adaptive sensor arrays is introduced. It is shown to have the capability of converging substantially faster than the nondeflected stochastic gradient (LMS) algorithm b...
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A new deflected stochastic-gradient algorithm for adaptive sensor arrays is introduced. It is shown to have the capability of converging substantially faster than the nondeflected stochastic gradient (LMS) algorithm but slower than the recursive least squares (RLS) algorithm. Because of its amenability to reduction of computational complexity by data quantization, it has the potential for processing digital signals with bandwidths one to two orders of magnitude larger than the bandwidths manageable with the RLS algorithm for sensor arrays containing a number of adjustable weights in the approximate range of 10-50.
The concept of fast KL transform coding introduced earlier [7], [8] for first-order Markov processes and certain random fields has been extended to higher order autoregressive (AR) sequences and practical images yield...
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The concept of fast KL transform coding introduced earlier [7], [8] for first-order Markov processes and certain random fields has been extended to higher order autoregressive (AR) sequences and practical images yielding what we call recursive block coding (RBC) algorithms. In general, the rate-distortion performance for these algorithms is significantly superior to that of the conventional block KL transform algorithm. Moreover, these algorithms permit the use of small size transforms, thereby removing the need for fast transforms and making the hardware implementation of such coders more appealing. This improved performance has been verified for practical image data and results in suppression of the block-boundary effect commonly observed in traditional transform coding techniques. This is illustrated by comparing RBC with cosine transform coding using both one- and twodimensional algorithms. Examples of RBC encoded images at various rates are given.
The importance of the concept of cyclostationarity in design and analysis of signal detectors, synchronizers, and extractors in communication systems is briefly discussed, and the central role of spectral correlation,...
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The importance of the concept of cyclostationarity in design and analysis of signal detectors, synchronizers, and extractors in communication systems is briefly discussed, and the central role of spectral correlation, in the characterization of random processes that are cyclostationary in the wide sense, is explained. A spectral correlation function that is a generalization of the power spectral density function is described, and a corresponding generalization of the Wiener-Khinchine relation and several other fundamental spectral correlation relations also are described. Explicit formulas for the spectral correlation function for various types of analog-modulated signals are derived. This includes pulse and carrier amplitude modulation, quadrature amplitude carrier modulation, and phase and frequency carrier modulation. To illustrate the differing spectral correlation characteristics of different modulation types, the magnitudes of the spectral correlation functions are graphed or described in graphical terms as the heights of surfaces above a bifrequency plane.
As a continuation of Part I, the spectral correlation function is presented for a variety of types of digitally modulated signals. These include digital pulse-amplitude, pulse-width, and pulse-position modulation, and...
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As a continuation of Part I, the spectral correlation function is presented for a variety of types of digitally modulated signals. These include digital pulse-amplitude, pulse-width, and pulse-position modulation, and various types of phase-shift keying and frequency-shift keying. The magnitudes of the spectral correlation functions are graphed as the heights of surfaces above a bifrequency plane, and these graphs are used as visual aids for comparison and contrast of the spectral correlation properties of different modulation types.
A method for estimation of the difference in the times of arrival of wavefronts of two separate sensors is introduced. The method, called SPECCORR, exploits the spectral correlation property, called spectral coherence...
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A method for estimation of the difference in the times of arrival of wavefronts of two separate sensors is introduced. The method, called SPECCORR, exploits the spectral correlation property, called spectral coherence, that essentially all modulated signals exhibit to obtain estimates that are highly tolerant to severely corruptive noise and interference. This tolerance is explained theoretically and demonstrated with simulations.< >
The unifying framework of the spectral-correlation theory of cyclostationary signals is used to present a broad treatment of weak, random signal detection for interception purposes. The relationships among a variety o...
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The unifying framework of the spectral-correlation theory of cyclostationary signals is used to present a broad treatment of weak, random signal detection for interception purposes. The relationships among a variety of previously proposed ad hoc detectors, optimum detectors, and newly proposed detectors are established. The spectral-correlation-plane approach to the interception problem is put forth as especially promising for detection, classification, and estimation in particularly difficult environments involving unknown and changing noise levels and interference activity. A fundamental drawback of the popular radiometric methods in such environments is explained.
Upper and lower bounding first-order linear recursions for the mean-squared error realized with the LMS algorithm subjected to a sequence of independent nonstationary training vectors are derived. These bounds coincid...
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Upper and lower bounding first-order linear recursions for the mean-squared error realized with the LMS algorithm subjected to a sequence of independent nonstationary training vectors are derived. These bounds coincide to give the exact evolution of mean-squared error for the problem of identification of a nonrecursive time-varying system with white-noise excitation. This leads to an exact formula for time-averaged mean-squared error that is used to study optimization of the step-size parameter for minimum time-average misadjustment. New results on dependence of the minimal step size and the minimum misadjustment on the degree of nonstationarity are obtained.
The control of hybrid systems is considered where a totally observed state process is generated by a nonlinear stochastic differential equation whose parameters are functions of a random jump process, called the plant...
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The control of hybrid systems is considered where a totally observed state process is generated by a nonlinear stochastic differential equation whose parameters are functions of a random jump process, called the plant regime. Regime transitions typically represent target maneuvers in a tracking system. The control task is split between a jump detection and identification (JDI) filter and a discrete adaptation, or reconfiguration. A design is presented that takes into account the errors of the JDI device and the plant nonlinearities to produce a near optimal passively adaptive control law with an easily implemented affine structure.
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