Genetic Synthesis of Signal Processing Networks Utilizing Diploid/Dominance

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@PhdThesis{greene:thesis,
  author =       "Francis Manwell Greene",
  title =        "Genetic Synthesis of Signal Processing Networks
                 Utilizing Diploid/Dominance",
  school =       "Department of Electrical Engineering. University of
                 Washington",
  year =         "1997",
  address =      "Seattle, USA",
  month =        "6 " # mar,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "https://digital.lib.washington.edu/dspace/handle/1773/4915/browse?rpp=20&etal=-1&type=title&starts_with=G&order=ASC&sort_by=1",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/fgPhdDissertation.pdf",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/fgDissertation.pdf",
  size =         "183 pages",
  abstract =     "Dissertation Proposal (July 29,
                 2001)

                 Introduction

                 This proposal is a result of research over the past two
                 years, and whose purpose was to develop a design
                 methodology for low cost ultrasonic blood flow and
                 tissue quantification using signal processing. My
                 original desire was to improve feature extraction
                 techniques for use in statistical pattern recognition,
                 but was almost immediately redirected along the lines
                 of efficient genetic search of network solution spaces.
                 Over ten years of experience with Doppler flow
                 measurement suggests that dynamic processing of the
                 clinical signals involved can be done with
                 interconnected functional elements such as delays,
                 filters, and thresholds. Some details of the processing
                 issues and reasons for using genetic search will
                 follow. The point of this dissertation is to study and
                 develop a specific method for synthesising processing
                 networks that aid in the use, interpretation, and
                 diagnostic power of low-cost medical
                 technology.

                 Conclusions

                 Results of synthesising a signal processing network
                 that correctly recognises fiducial points in a
                 simulated two-heart cycle, spectrally represented, wave
                 form suggests the ability to handle similar
                 applications with real clinical Doppler data. The
                 solution described in the previous section made use of
                 a delay element that matches the heart-cycle period and
                 is otherwise sensible. Search difficulty was increased
                 by including in the function set a number of
                 function/operators not actually needed to solve the
                 problem. This was done purposely to eliminate the
                 necessity of defining a problem dependent function set
                 as may be necessary for medical data.

                 A multiple trial, multi-modal, partially deceptive test
                 problem provide further evidence that the Max(f1,f2)
                 diploid/dominance implementation can provide better
                 than or equal processing efficiency, compared to
                 haploid. This conclusion is supported by a similar,
                 though less thorough, comparison using the R-wave
                 network synthesis problem. The Max(f1,f2) approach has
                 been observed to do about the same as haploid with
                 either very simple (e.g., unimodal) or very difficult
                 or poorly formulated problems. Diploid/dominance as
                 implemented here can be used in conjunction with other
                 improvements (e.g., more refined crossover, inversion,
                 species formation, etc.) to the standard GA. The
                 experiments with alternating fitness environments show
                 that multiploid populations are capable of storing and
                 rapidly recalling as many global optima as there are
                 homologues in each individual chromosome and shows that
                 diploid/dominance retains recessive alleles and
                 schema.

                 The diploid approach could immediately make use of a
                 two-processor system, since the algorithm used involves
                 two function evaluations per generations.",
  notes =        "Supervisior Dr. Alistair Holden. fgDissertation.pdf is
                 Dissertation Proposal (July 29, 2001)",
}

Genetic Programming entries for Francis Greene

Citations