@conference {
	title = {Model-Based ATR:  Algorithms Based on Reduced Target Models, Learning and Probing},
	author = {Baras, John S., MacEnany, David C.},
	year = {1992},
	month = {03/1992},
	abstract = {Two new model based ATR algorithms are presented. The algorithms employ economic target models, recent mathematical developments in the extraction and reduction of target silhouettes from noisy images, and on-line probing for clutter reduction and target classification. The target models used employ a small, carefully selected set of characteristic viewpoints and local features. The design of the algorithms are described and their performance evaluated using synthetic FLIR data. The two algorithms are: the Probing Algorithm and the 4-Way Distance Algorithm. Both algorithms have an early phase which is primarily statistical, and a late phase which is primarily geometric, although the two phases are tightly coupled, with frequent revisitation of the image data used to increase decision confidence. In the Probing Algorithm novel on-line probing is performed using stored target geometric models to efficiently implement a generalized maximum likelihood principle. The Probing Algorithm self-adapts to find the most appropriate target location, range and viewpoint geometry and then performs decision-making based on selected maximum likelihood estimates and on-line computed, optimal probing sets. The 4-Way Distance Algorithm performs decision making based on a classification tree logic utilizing matching scores computed on four components of the target silhouette.},
	address = {Ft. Belvoir, Virginia},
	booktitle = {Second ATR Systems and Technology Conference},
	pages = {pp. 277-300}
}
@conference {
	title = {Scale-Space Polygonalization of Target Silhouettes and Applications to Model-Based ATR},
	author = {MacEnany, David C., Baras, John S.},
	year = {1992},
	month = {03/1992},
	abstract = {Economic descriptions of shapes and objects are essential for model based ATR. In addition to object silhouettes, geometric features such as corners and simplified representations such as polygonal approximations can be used to reduce shape description complexity. Here we analyze the polygonal approximation of object silhouette boundaries. Robust polygonalization for ATR requires the construction of polygonal approximations in various scales; namely polygons preserving features of the boundary with varying resolution. In this paper we introduce the notion of scalespace polygonalization. Scale-space polygonalization allows for the generation of polygonal approximations across a range of resolutions and achieve vertex localization which is uniform in scale. The notion of scale or resolution for a polygon involves the distances between its vertices and the magnitude of its vertex angles. Fine scale implies high resolution of the details of boundary contours while coarse scale implies only gross details of boundary contours with a consequent reduction of both computational and descriptive complexity. The polygonalization methods and algorithms presented here are novel in that we control the reduction of the contour complexity by adjusting resolution parameters which have a natural interpretation and achieve vertex localization which is uniform in scale and persistent in scale. These polygonalized boundaries can be used to generate a target fingerprint across a range of scales. Scale-space polygons are important for ATR because they provide a way to reduce the complexity of digitized planar curves consisting of polygons having hundreds of sides to polygons of about a dozen sides, while still capturing the essential features of the model silhouette. This is desirable because shorter polygonal descriptions yield faster correlations and matchings and reduce the overall computational complexity of the ATR problem. We show how scale-space polygonalization can be used to obtain efficient representations of targets, and fast matching algorithms. We also show how scale-space polygons can be used to obtain stable edges from noisy images. We demonstrate these results on examples involving synthetic FLIR data and CAD target models.},
	address = {Ft. Belvoir, Virginia},
	booktitle = {Second ATR Systems and Technology Conference},
	pages = {pp. 223-247}
}
@conference {
	title = {Fast Error-Free Algorithms for Polynomial Matrix Computations},
	author = {Baras, John S., MacEnany, David C., Munach, Robert Lawrence.},
	year = {1990},
	month = {12/1990},
	abstract = {Matrices of polynomials over rings and fields provide a unifying framework for many control system design problems. These include dynamic compensator design, infinite dimensional systems, controllers for nonlinear systems, and even controllers for discrete events stems. An important obstacle for utilizing these powerful mathematical tools in practical applications has been the non-availability of accurate and efficient algorithms to carry through the precise error-free computations required by these algebraic methods. In this paper we develop highly efficient, error-free algorithms, for most of the important computations needed in near systems over fields or rings. We show that the structure of the underlying rings and modules is critical in designing such algorithms.},
	address = {Honolulu, Hawaii},
	booktitle = {The 29th Conference on Decision and Control (CDC)},
	pages = {pp. 941-946}
}
@conference {
	title = {Bayesian Sequential Hypothesis Testing},
	author = {Baras, John S., MacEnany, David C.},
	year = {1990},
	month = {08/1990},
	abstract = {We consider the Bayesian sequential detection problem for general observation processes with a continuous time parameter. Primary emphasis is placed on first exit policies and their generic optimality. A new geometric formulation and solution to the existence and uniqueness of the optimal first exit policy will be given as well as an explicit constructive algorithm for its computation. We will apply these resuits to the problem of Bayesian sequential detection for diffusion-type observations although our methods and results generalize to problems of optimal stopping and decision for partially observed Markov chains where the observation processes are of the diffusion or point process type. These results will appear elsewhere.},
	address = {Tallin, USSR},
	booktitle = {The 11th IFAC World Congress},
	pages = {pp. 227-232}
}
@conference {
	title = {Efficient Computer Algebra Algorithms for Polynomial Matrices in Control Design},
	author = {Baras, John S., MacEnany, David C., Munach, Robert Lawrence.},
	year = {1989},
	month = {08/1989},
	abstract = {The theory of polynomial matrices plays a key role in the design and analysis of multi-input multi-output control and communications systems using frequency domain methods. Examples include coprime factorizations of transfer functions, canonical realizations from matrix fraction descriptions, and the transfer function design of feedback compensators. Typically, such problems abstract in a natural way to the need to solve systems of Diophantine equations (the so-called generalized Bezout equations) or systems of linear equations over polynomials. These and other problems involving polynomial matrices can in turn be reduced to polynomial matrix triangularization procedures, a result which is not surprising given the importance of matrix triangularization techniques in numerical linear algebra. - There, we deal with matrices with entries from a field and Gaussian elimination plays a fundamental role in understanding the triangularization process. In the case of polynomial matrices we are dealing with matrices with entries from a ring for which Gaussian elimination is not defined and triangularization is accomplished by what is quite properly~called Euclidean elimination.

~Unfortunately, the numerical stability and sensitivity issues which accompany floatingpoint approaches to Euclidean elimination are not very well understood at present. In~this paper we present new algorithms which circumvent entirely such numerical issues through the use of exact, symbolic methods in computer algebra. The use of such error-free algorithms guarantees that the results are accurate to within the precision of the model data-the best that can be hoped. Care must be taken in the design of such algorithms due to the phenomenon of intermediate epression swell, the price paid for freedom from roundoff error. The emphasis will be placed on efficient algorithms to compute exact Hermite forms for polynomial matrices because this triangularization procedure is central to a large variety of algorithms important in the design of control and communication systems. Moreover, the triangular Hermite form is defined for any matrix with entries from a principal ideal ring and such matrices arise in many practical problems in communications and control, such as the design of convolutional coders and the analysis of quantization effects in linear systems. Due to their symbolic nature, our algorithms apply equally well to such problems since the particular ring involved in a problem can itself be considered~as program input data.},
	address = {Oxnard, California},
	booktitle = {The 3rd Annual Conference on Aerospace Computational Control},
	pages = {pp. 292}
}
@conference {
	title = {Fast Algorithms for the Triangularization of Polynomial Matrices},
	author = {Baras, John S., MacEnany, David C.},
	year = {1989},
	month = {05/1989},
	abstract = {The theory of polynomial matrices plays a key role in the design and analysis of multi-input-multi-output control systems. More generally, matrices with entries from various principal ideal rings arise in many practical problems in communications and control, such as the design of convolutional coders and the analysis of computational aspects which accompany such matrices are not widely appreciated at present. Indeed, one popularly held belief is that polynomial matrix problems are merely "big" linear algebra problems, but are otherwise essentially straightforward from a numerical standpoint. However, time and again, when confronted by real-world data, the best algorithms of linear algebra fail miserably despite meticulous program design and use of multiple precision floating-point arithmetic. We will describe the nature of this unexpectedly bad behavior and present new algorithms which circumvent it entirely through the use of exact, symbolic methods in computer algebra. Emphasis will be placed on efficient algorithms to compute exact Hermite forms for polynomial matrices because this triangularization procedure is central to a large variety of algorithms important in the design of control and communication systems},
	address = {San Francisco, California},
	booktitle = {The SIAM Conference on Control in the 90{\textquoteright}s: Achievements, Opportunities, and Challenges},
	pages = {pp. 301}
}
@conference {
	title = {Sequential Testing on the Rate of a Counting Process},
	author = {Baras, John S., MacEnany, David C.},
	year = {1987},
	month = {12/1987},
	abstract = {In this paper, optimality results are given for the problems of Bayesian and Wald sequential (simple, binary) hypothesis testing on the rate of a counting process. An explicit formula is given for the Bayes risk, and the system to solve for the exact optimal thresholds is also given.},
	address = {Los Angeles, California},
	booktitle = {The 26th IEEE Conference on Decision and Control},
	pages = {pp. 1592-1593}
}
@conference {
	title = {The DELPHI System:  A System Level Tool for Integrated Design of Real-Time Signal Processors},
	author = {Baras, John S., Ebrahimi, Fariborz., Israel, Bruce., LaVigna, Anthony., MacEnany, David C.},
	year = {1987},
	month = {08/1987},
	address = {San Diego, CA},
	booktitle = {SPIE{\textquoteright}s 31st Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, in Real Time Signal Processing X},
	pages = {pp. 10-14}
}
