TEStool: an environment for visual interactive modeling of autocorrelated traffic

Geist, Daniel; Melamed, Benjamin

doi:10.1109/icc.1992.268033

Cited by 27 publications

(12 citation statements)

References 11 publications

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“…TEStool is a visual interactive software environment designed to support the construction and modification of TES models, to generate simulated sample paths from the models, and to examine their statistics (Geist andMelamed 1992, Melamed et al 1992).…”

Section: The Testool Modeling Softwarementioning

confidence: 99%

Applications of the TES modeling methodology

Melamed¹,

Hill²

1993

Proceedings of the 25th Conference on Winter Simulation - WSC '93

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TES (Transform-Expand-Sample)is a versatile methodology for modeling general stationary time series, and particularly those that are autocorrelated. The salient feature of TES lies in its ability to simultaneously capture firstorder and second-order properties of empirical time series ; given a sample data sequence, TES is designed to simultaneously capture any arbitrary marginal distribution and approximate the leading autocorrelations. Practical TES modeling is computationally intensive and can be effectively carried out only with software support. A computerized modeling environment, TEStool, has been designed to support the TES modeling methodology, through an interactive heuristic search approach facilitated by stateof-the-art data visualization techniques. The purpose of this paper is to present four examples of the effective use of the TES methodology to model various types of time series that arise in a variety of disciplines, ranging from manufacturing to financial modeling, with particular emphasis on video compression. These examples serve to highlight the efficacy and versatility of the TES modeling methodology.

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Section: The Testool Modeling Softwarementioning

confidence: 99%

Applications of the TES modeling methodology

Melamed¹,

Hill²

1993

Proceedings of the 25th Conference on Winter Simulation - WSC '93

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“…TEStool is a visual interactive software environment designed for fitting TES models to empirical data [7,27,9]. It provides services to construct and modify TES models in the heuristic search mode, to generate simulated sample paths and to examine their statistics, as well as to launch algorithmic searches.…”

Section: The Testool Modeling Envirorunentmentioning

confidence: 99%

“…Consequently, TES modeling of empirical data may be carried out interactively and visually. This observation motivated the design and implementation of a TES-based modeling package, called TEStool, which makes heavy use of visualization in order to provide a pleasant interactive environment for modeling dependent stationary time series [7,9]. Two search approaches have been implemented: heuristic and algorithmic.…”

Section: Introductionmentioning

confidence: 99%

A Survey of TES Modeling Applications

Melamed¹,

Hill²

1995

SIMULATION

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Princeton, NJ 08540 TES (Transform-Expand-Sample) is a versatile methodology for modeling general stationary time series, and particularly those that are autocorrelated. From the viewpoint of Monte Carlo simulation, TES represents a new and flexible input analysis approach. The salient feature of TES is its potential ability to simultaneously capture first-order and second-order properties of empirical time series (field measurements): Given an empirical sample, TES is designed to fit an arbitrary empirical marginal distribution (histogram) and to simultaneously approximate the leading empirical autocorrelations. Practical TES modeling is computationally intensive and can be effectively carried out only with computer support. A software modeling environment, called TEStool, has been designed and implemented to support the TES modeling methodology, through an interactive heuristic or algorithmic search approach employing extensive visualization. The purpose of this paper is to introduce TES modeling, and to offer some illustrative examples from a range of applications, including source modeling of compressed video and fault arrivals, financial modeling and texture generation. These examples demonstrate the efficacy and versatility of the TES modeling methodology, and underscore the high fidelity attainable with TES models.

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“…In addition, a big advantage of TES processes is that autocorrelation functions can be calculated using a mathematical formula which makes the modeling phase faster. TEStool [9] is a graphical user interface that allows modeling stationary sequences using the TES methodology.…”

Section: Overview Of the Mpeg4 Video Encoding Standardmentioning

confidence: 99%

“…The last step results in a distorted background sequence which is then inverted to a foreground sequence using the inverse of the histogram distribution which always guarantees the matching of the marginals. The task of finding an appropriate innovation density that approximates the empirical autocorrelation is carried out via a heuristic search using TEStool [9].…”

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confidence: 99%

Low bit-rate video transmission over wireless Zigbee networks

Zainaldin¹

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TEStool: an environment for visual interactive modeling of autocorrelated traffic

Cited by 27 publications

References 11 publications

Applications of the TES modeling methodology

Applications of the TES modeling methodology

A Survey of TES Modeling Applications

Low bit-rate video transmission over wireless Zigbee networks

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