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Pattern Recognition

Este es un curso introductorio que cubre algunos de los temas más fundamentales de reconocimiento de patrón de cadena. Habrá una descripción general de los temas, pero no habrá un debate en profundidad de cada uno. En su lugar, el curso pretende dar al estudiante una visión general del campo.


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Paco Gómez Martín

 

Escuela Universitaria de Informática

Asignatura optativa y de libre elección en Ingeniería de Sistemas e Ingeniería de Gestión; troncal en el título de Experto en Algorítmica Aplicada a la Empresa y la Industria.

Last review: July 2010.

 

Valora esta asignatura

Duración: 4 ECTS.

 

REQUIREMENTS AND PRIOR KNOWLEDGE

There is no formal prerequisites for this course.

 

GENERAL DESCRIPTION OF THE SUBJECT

This is an introductory course that covers some of the most fundamental topics of exact string pattern recognition. There will be general descriptions of those topics, but there will not be an in-depth discussion of each. Instead, the course is intended to give the student an overview of the field.

 

OBJETIVES: KNOWLEDGE AND SKILLS

The goals of this course include:

  1. To know the theoretical and algorithmic foundations of exact string pattern recognition.
  2. To provide the students with a hands-on approach that will include their knowing practical issues involved in the programming of patternrecognition algorithms.
  3. To know the main applications of exact string pattern recognition to other problems in computer science.
  4. To know some applications of exact string pattern recognition to problems found in other fields, in particular, in Computational Biology and Computational Music Theory.

 

TEACHING MATERIAL

Course notes written by Paco Gomez.

 

EVALUATION ACTIVIVTIES OR PRACTICALT ASKS

  • For the February examination session:
    1. Attendance of the 75% of sessions is required.
    2. Course grade will be assigned based on scores on four homework assignments. There will be both theoretical and practical (programming) assignnments. There will at least 4 assignments and at most 6, depending on time and pace.
    3. Each assignment will have the same weight over the final grade.
    4. One of the assignments will consist of a programming project.
    5. A pass is obtained with 50 points over 100.
  • For the other examination sessions students will have to hand over a project (60%) and write an exam (40%).

 

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Copyright 2009, Autores y colaboradores. Reconocer autoría/Citar obra. Martín, P. G. (2010, March 08). Pattern Recognition. Retrieved October 21, 2017, from OCW UPM - OpenCourseWare de la Universidad Politécnica de Madrid Web site: http://ocw.upm.es/ciencia-de-la-computacion-e-inteligencia-artificial/pattern-recognition. Esta obra se publica bajo una licencia Licencia Creative Commons Licencia Creative Commons