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1. Sample reference to "Reducing the computational cost of local search in the hybrid evolutionary algorithm with application to electronic imaging"

Professor Gertner's research interests are in the areas of Automatic Target Recognition, Time-Frequency Analysis, Hardware/Software co-design of real-time algorithms, Evolutionary Algorithms, Semantic Web. My research activities are supported by MDA. Former funding has been provided by ONR, AFRL, and MDA.

• I. Gertner, G.A. Geri, “A weighted Zak Transform, Its Properties,, and Applications to Signal processing” in PHYSICS OF AUTOMATIC TARGET RECOGNITION, Ed. F.Sadjadi, pp.57-72, Springer, 2007.
• I.V. Maslov, I.Gertner, “Multisensor Target Recognition in Image Response Space Using Evolutionary Algorithms” in PHYSICS OF AUTOMATIC TARGET RECOGNITION, Ed. F.Sadjadi, pp.127-142, Springer, 2007.
• I.V. Maslov, I. Gertner, Multi-Sensor fusion: An evolutionary algorithm approach, INFORMATION FUSION, 7, pp.304-330, July 2006.
• I.A. Maslov, I. Gertner, “Reducing the computational cost of local search in the hybrid evolutionary algorithm with application to electronic imaging”. Engineering Optimization, Vol. 37, No.1, January, 2005, pp. 103-119.
• I.A. Maslov, I. Gertner, " OBJECT RECOGNITION WITH THE HYBRID EVOLUTIONARY ALGORITHM : A Novel Response Analysis Approach”,Journal Of Optical Engineering- A Special Issue On Home-Land Security, Vol. 43. No.10,October 2004.
• J. Wei and I. Gertner, “MRF-MAP-MFT visual object segmentation based on motion boundary field ”. Pattern Recognition Letters, 24, 2003, pp. 3125-3139.

Sample references:

. "Reducing the computational cost of local search in the hybrid evolutionary algorithm with application to electronic imaging"

. "Multi-Sensor Fusion: an  Evolutionary Algorithm Approach"