Estimation of Target Behavior Tendencies using DSmT

Estimation of Target Behavior Tendencies using DSmT
Author: Albena Tchamova
Publisher: Infinite Study
Total Pages: 14
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This chapter presents an approach for target behavior tendency es timation (Receding, Approaching). It is developed on the principles of Dezert Smarandache theory (DSmT) of plausible and paradoxical reasoning applied to conventional sonar amplitude measurements, which serve as an evidence for corresponding decision-making procedures.

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Publisher: IOS Press
Total Pages: 6097
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Advances and Applications of DSmT for Information Fusion (Collected works)

Advances and Applications of DSmT for Information Fusion (Collected works)
Author: Florentin Smarandache
Publisher: Infinite Study
Total Pages: 438
Release: 2004
Genre: Computers
ISBN: 1931233829

Papers collected from researchers in fusion information, such as: Florentin Smarandache, Jean Dezert, Hongshe Dang, Chongzhao Han, Frederic Dambreville, Milan Daniel, Mohammad Khoshnevisan, Sukanto Bhattacharya, Albena Tchamova, Tzvetan Semerdjiev, Pavlina Konstantinova, Hongyan Sun, Mohammad Farooq, John J. Sudano, Samuel Corgne, Gregoire Mercier, Laurence Hubert-Moy, Anne-Laure Jousselme, Patrick Maupin and others on Dezert-Smarandache Theory of Plausible and Paradoxical Reasoning (DSmT).. The principal theories available until now for data fusion are the probability theory, the fuzzy set theory, the possibility theory, the hint theory and the theory of evidence. Since last two years J. Dezert and F. Smarandache are actively developing a new theory of plausible and paradoxical reasoning, called DSmT (acronym for Dezert-Smarandache Theory), for information fusion of uncertain and highly conflicting sources of information. The DSmT can be interpreted as a generalization of the Dempster-Shafer Theory (DST) but goes far beyond the DST. The free-DSmT model, which assumes that the ultimate refinement of the frame of discernment of the fusion problem is not accessible due to the intrinsic nature of its elements, is opposite to the Shafer's model (on which is based the DST) assuming the exhaustivity and exclusivity of all elements of the frame of discernment. The DSmT proposes a new theoretical framework for data fusion based on definition of hyper-power sets and a new simple commutative and associative rule of combination. Recently, it has been discovered, through a new DSm hybrid rule of combination, that DSmT can be also extended to problems involving hybrid-models (models including some exclusivity and/or non-existentially constraints). This new important theoretical result offers now to the DSmT a wider class of fusion applications and allows potentially to attack the next generation of complex dynamical/temporal fusion problems. DSmT can also provide a theoretical issue for the fusion of neutrosophic information (extension of fuzzy information proposed by F. Smarandache in nineties - see http://www.gallup.unm.edu/~smarandache/FirstNeutConf.htm for details about the neutrosophy logic and neutrosophy set theory).

Advances and Challenges in Multisensor Data and Information Processing

Advances and Challenges in Multisensor Data and Information Processing
Author: E. Lefebvre
Publisher: IOS Press
Total Pages: 412
Release: 2007-05-11
Genre: Business & Economics
ISBN: 1607502321

Information fusion resulting from multi-source processing, often called multisensor data fusion when sensors are the main sources of information, is a relatively young (less than 20 years) technology domain. It provides techniques and methods for: Integrating data from multiple sources and using the complementarity of this data to derive maximum information about the phenomenon being observed; Analyzing and deriving the meaning of these observations; Selecting the best course of action; and Controlling the actions. Various sensors have been designed to detect some specific phenomena, but not others. Data fusion applications can combine synergically information from many sensors, including data provided by satellites and contextual and encyclopedic knowledge, to provide enhanced ability to detect and recognize anomalies in the environment, compared with conventional means. Data fusion is an integral part of multisensor processing, but it can also be applied to fuse non-sensor information (geopolitical, intelligence, etc.) to provide decision support for a timely and effective situation and threat assessment. One special field of application for data fusion is satellite imagery, which can provide extensive information over a wide area of the electromagnetic spectrum using several types of sensors (Visible, Infra-Red (IR), Thermal IR, Radar, Synthetic Aperture Radar (SAR), Polarimetric SAR (PolSAR), Hyperspectral...). Satellite imagery provides the coverage rate needed to identify and monitor human activities from agricultural practices (land use, crop types identification...) to defence-related surveillance (land/sea target detection and classification). By acquiring remotely sensed imagery over earth regions that land sensors cannot access, valuable information can be gathered for the defence against terrorism. This books deals with the following research areas: Target recognition/classification and tracking; Sensor systems; Image processing; Remote sensing and remote control; Belief functions theory; and Situation assessment.

On the generation of hyper-powersets for the DSmT

On the generation of hyper-powersets for the DSmT
Author: Jean Dezert
Publisher: Infinite Study
Total Pages: 11
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ISBN:

The recent theory of plausible and paradoxical reasoning (DSmT) developed by the authors appears to be a nice promising theoretical tools to solve many information fusion problems where the Shafer’s model cannot be used due to the intrinsic paradoxical nature of the elements of the frame of discernment and where a strong internal conflict between sources arises.

FUSION ...

FUSION ...
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Publisher:
Total Pages: 810
Release: 2003
Genre: Automatic tracking
ISBN:

Information Fusion on Belief Networks

Information Fusion on Belief Networks
Author: Shawn C. Eastwood
Publisher: Infinite Study
Total Pages: 28
Release:
Genre: Mathematics
ISBN:

This paper will focus on the process of “fusing” several observations or models of uncertainty into a single resultant model. Many existing approaches to fusion use subjective quantities such as “strengths of belief” and process these quantities with heuristic algorithms. This paper argues in favor of quantities that can be objectively measured, as opposed to the subjective “strength of belief” values. This paper will focus on probability distributions, and more importantly, structures that denote sets of probability distributions known as “credal sets”. The novel aspect of this paper will be a taxonomy of models of fusion that use specific types of credal sets, namely probability interval distributions and Dempster-Shafer models.

Automatic goal allocation for a planetary rover with DSmT

Automatic goal allocation for a planetary rover with DSmT
Author: Massimiliano Vasile
Publisher: Infinite Study
Total Pages: 25
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In this chapter, we propose an approach for assigning an interest level to the goals of a planetary rover. Assigning an interest level to goals, allows the rover to autonomously transform and reallocate the goals.

Advances and Applications of DSmT for Information Fusion, Vol. 3

Advances and Applications of DSmT for Information Fusion, Vol. 3
Author: Florentin Smarandache
Publisher: Infinite Study
Total Pages: 760
Release: 2004
Genre: Science
ISBN: 1599730731

This volume has about 760 pages, split into 25 chapters, from 41 contributors. First part of this book presents advances of Dezert-Smarandache Theory (DSmT) which is becoming one of the most comprehensive and flexible fusion theory based on belief functions. It can work in all fusion spaces: power set, hyper-power set, and super-power set, and has various fusion and conditioning rules that can be applied depending on each application. Some new generalized rules are introduced in this volume with codes for implementing some of them. For the qualitative fusion, the DSm Field and Linear Algebra of Refined Labels (FLARL) is proposed which can convert any numerical fusion rule to a qualitative fusion rule. When one needs to work on a refined frame of discernment, the refinement is done using Smarandache¿s algebraic codification. New interpretations and implementations of the fusion rules based on sampling techniques and referee functions are proposed, including the probabilistic proportional conflict redistribution rule. A new probabilistic transformation of mass of belief is also presented which outperforms the classical pignistic transformation in term of probabilistic information content. The second part of the book presents applications of DSmT in target tracking, in satellite image fusion, in snow-avalanche risk assessment, in multi-biometric match score fusion, in assessment of an attribute information retrieved based on the sensor data or human originated information, in sensor management, in automatic goal allocation for a planetary rover, in computer-aided medical diagnosis, in multiple camera fusion for tracking objects on ground plane, in object identification, in fusion of Electronic Support Measures allegiance report, in map regenerating forest stands, etc.

The Generalized Pignistic Transformation

The Generalized Pignistic Transformation
Author: Jean Dezert
Publisher: Infinite Study
Total Pages: 11
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This paper presents in detail the generalized pignistic transformation (GPT)succinctly developed in the Dezert-Smarandache Theory (DSmT) framework as a tool for decision process. The GPT allows to provide a subjective probability measure from any generalized basic belief assignment given by any corpus of evidence. We mainly focus our presentation on the 3D case and provide the complete result obtained by the GPT and its validation drawn from the probability theory.