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Author

Victor S. Frost

Other affiliations: National Science Foundation
Bio: Victor S. Frost is an academic researcher from University of Kansas. The author has contributed to research in topics: Asynchronous Transfer Mode & Radar imaging. The author has an hindex of 24, co-authored 148 publications receiving 4297 citations. Previous affiliations of Victor S. Frost include National Science Foundation.


Papers
More filters
Journal ArticleDOI
TL;DR: A model for the radar imaging process is derived and a method for smoothing noisy radar images is presented and it is shown that the filter can be easily implemented in the spatial domain and is computationally efficient.
Abstract: Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.

1,906 citations

Journal ArticleDOI
TL;DR: An overview of discrete event simulation is given and two important modelling issues that are germane to extant and emerging networks: traffic modelling and rare event simulation are singled out.
Abstract: As new communications services evolve, professionals must create better models to predict system performance. The article provides an overview of computer simulation modelling for communication networks, as well as some important related modelling issues. It gives an overview of discrete event simulation and singles out two important modelling issues that are germane to extant and emerging networks: traffic modelling and rare event simulation. Monte Carlo computer simulation is used as a performance prediction tool and Markov models are considered. >

595 citations

Journal ArticleDOI
TL;DR: The current trend is to provide Internet access to passengers on trains using IEEE 802.11; however, a clear method for connecting trains to the global Internet has yet to emerge.
Abstract: We present a survey of approaches for providing broadband Internet access to trains. We examine some of the barriers that hinder the use of broadband Internet on trains and then discuss some of the opportunities for broadband deployment to trains. This survey considers some of the basic concepts for providing broadband Internet access and then reviews associated network architectures. The review of network architectures shows that we can subdivide networks for providing broadband Internet access to trains into the train-based network, the access network-for connecting the train to the service provider(s)-and the aggregation network-for collecting user packets generated in the access network for transmission to the Internet. Furthermore, our review shows that the current trend is to provide Internet access to passengers on trains using IEEE 802.11; however, a clear method for connecting trains to the global Internet has yet to emerge. A summary of implementation efforts in Europe and North America serves to highlight some of the schemes that have been used thus far to connect trains to the Internet. We conclude by discussing some of the models developed, from a technical perspective, for testing the viability of deploying Internet access to trains.

151 citations

Journal ArticleDOI
TL;DR: A procedure for extracting a set of textural features for characterizing small areas in radar images is presented and it is shown that these features can be used for classifying segments of radar images corresponding to different geological formations.
Abstract: Texture is an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in the analysis of a variety of photographic images, they have not been used for processing radar images. In this paper, we present a procedure for extracting a set of textural features for characterizing small areas in radar images and show that these features can be used for classifying segments of radar images corresponding to different geological formations.

99 citations

Journal ArticleDOI
TL;DR: The authors discuss the control of short-term congestion in integrated packet networks (IPNs) containing a mix of data, speech, and possibly other types of signals with a system model that assigns a delivery priority to each packet at the transmitter and discards speech packets according to delivery priority at any point in the network in response to overload.
Abstract: The authors discuss the control of short-term congestion, which is referred to as overload, in integrated packet networks (IPNs) containing a mix of data, speech, and possibly other types of signals. A system model is proposed that assigns a delivery priority to each packet (speech or otherwise) at the transmitter and discards speech packets according to delivery priority at any point in the network in response to overload. This model attempts to minimize per-packet processing at networks nodes. The research described is guided by two principles for IPN design: minimal per-packet processing and flexibility due to signal structure. The quality of the received speech is maintained by classifying speech segments according to their structure and coding them in a way that ensures ease of lost-packet regeneration at the receiver. The results of an experiment are reported that confirmed the general validity of this model from the standpoint of transmitter and receiver processing and subjective quality. >

90 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: It is found that user-initiated TCP session arrivals, such as remote-login and file-transfer, are well-modeled as Poisson processes with fixed hourly rates, but that other connection arrivals deviate considerably from Poisson.
Abstract: Network arrivals are often modeled as Poisson processes for analytic simplicity, even though a number of traffic studies have shown that packet interarrivals are not exponentially distributed. We evaluate 24 wide area traces, investigating a number of wide area TCP arrival processes (session and connection arrivals, FTP data connection arrivals within FTP sessions, and TELNET packet arrivals) to determine the error introduced by modeling them using Poisson processes. We find that user-initiated TCP session arrivals, such as remote-login and file-transfer, are well-modeled as Poisson processes with fixed hourly rates, but that other connection arrivals deviate considerably from Poisson; that modeling TELNET packet interarrivals as exponential grievously underestimates the burstiness of TELNET traffic, but using the empirical Tcplib interarrivals preserves burstiness over many time scales; and that FTP data connection arrivals within FTP sessions come bunched into "connection bursts", the largest of which are so large that they completely dominate FTP data traffic. Finally, we offer some results regarding how our findings relate to the possible self-similarity of wide area traffic. >

3,915 citations

01 Jan 2000
TL;DR: This article briefly reviews the basic concepts about cognitive radio CR, and the need for software-defined radios is underlined and the most important notions used for such.
Abstract: An Integrated Agent Architecture for Software Defined Radio. Rapid-prototype cognitive radio, CR1, was developed to apply these.The modern software defined radio has been called the heart of a cognitive radio. Cognitive radio: an integrated agent architecture for software defined radio. Http:bwrc.eecs.berkeley.eduResearchMCMACR White paper final1.pdf. The cognitive radio, built on a software-defined radio, assumes. Radio: An Integrated Agent Architecture for Software Defined Radio, Ph.D. The need for software-defined radios is underlined and the most important notions used for such. Mitola III, Cognitive radio: an integrated agent architecture for software defined radio, Ph.D. This results in the set-theoretic ontology of radio knowledge defined in the. Cognitive Radio An Integrated Agent Architecture for Software.This article first briefly reviews the basic concepts about cognitive radio CR. Cognitive Radio-An Integrated Agent Architecture for Software Defined Radio. Cognitive Radio RHMZ 2007. Software-defined radio SDR idea 1. Cognitive radio: An integrated agent architecture for software.Cognitive Radio SOFTWARE DEFINED RADIO, AND ADAPTIVE WIRELESS SYSTEMS2 Cognitive Networks. 3 Joseph Mitola III, Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio Stockholm.

3,814 citations

Journal ArticleDOI
TL;DR: A model for the radar imaging process is derived and a method for smoothing noisy radar images is presented and it is shown that the filter can be easily implemented in the spatial domain and is computationally efficient.
Abstract: Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.

1,906 citations

Journal ArticleDOI
TL;DR: This paper provides the derivation of speckle reducing anisotropic diffusion (SRAD), a diffusion method tailored to ultrasonic and radar imaging applications, and validates the new algorithm using both synthetic and real linear scan ultrasonic imagery of the carotid artery.
Abstract: This paper provides the derivation of speckle reducing anisotropic diffusion (SRAD), a diffusion method tailored to ultrasonic and radar imaging applications. SRAD is the edge-sensitive diffusion for speckled images, in the same way that conventional anisotropic diffusion is the edge-sensitive diffusion for images corrupted with additive noise. We first show that the Lee and Frost filters can be cast as partial differential equations, and then we derive SRAD by allowing edge-sensitive anisotropic diffusion within this context. Just as the Lee (1980, 1981, 1986) and Frost (1982) filters utilize the coefficient of variation in adaptive filtering, SRAD exploits the instantaneous coefficient of variation, which is shown to be a function of the local gradient magnitude and Laplacian operators. We validate the new algorithm using both synthetic and real linear scan ultrasonic imagery of the carotid artery. We also demonstrate the algorithm performance with real SAR data. The performance measures obtained by means of computer simulation of carotid artery images are compared with three existing speckle reduction schemes. In the presence of speckle noise, speckle reducing anisotropic diffusion excels over the traditional speckle removal filters and over the conventional anisotropic diffusion method in terms of mean preservation, variance reduction, and edge localization.

1,816 citations