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marine science courses
 
 
  Department of Marine Science | Courses | HYD 620 Math Concepts for Hydrographers
HYD 620 Math Concepts for Hydrographers

HYD 620 - Math. Concepts for Hydrographers


dotInstructor: Dr. Chung-Chu Teng; office hours are by appointment
Rm 353E, Bldg. 1100, SSC
       (228) 688-7101
       cteng@noaa.gov

dotTime: 8:30 a.m. - 10:30 a.m. Friday

dotPlace: Bldg. 8100

dotCourse objective: To provide a basic understanding of mathematical and statistical concepts needed for succeeding in hydrographic science.

dotCourse description: This course provides introduction and review of the mathematics and statistics necessary for field hydrographers. Topics covered in this course include linear algebra, probability, statistics, covariance and propagation, least squares methods and adjustments, error propagation, random processes, linear systems and filtering, etc. Practical and hands-on experience on the above topics are emphasized and conducted using the modern computing environment and package MATLAB. Basic operations of MATLAB is introduced at the beginning of the course.

dotCourse outline:

• MATLAB programming

• Linear algebra: vectors, matrices, linear equations, elimination and decomposition, Eigen values and vectors.

• Probability: random variables, discrete and continuous probability, descriptive measures of probability functions, normal distribution, multi-variate probability distribution

• Statistics: Frequency distribution, data description (measures of central tendency, dispersion, and distribution shapes), sampling and sampling distributions, Chi-square and t distributions, estimations, confidential intervals, hypothesis testing

• Errors, error propagation, linearization

• Variance and covariance, variance and covariance matrix, covariance propagation

• Least squares Techniques: Principles of least squares, least squares adjustments, the concept of weight, the dual problem, least squares for regression

• Random processes and Fourier analysis: random processes, Fourier series and integrals, discrete Fourier transform, spectral analysis, aliasing

• Kalman filtering: recursive least squares estimation, Kalman filter equations, recursive process, smoothing


dotGrading: Grades (A-F) will be awarded based upon completion of problem sets that will be assigned following each lecture.

dotTextbook: None. Handouts and reference material will be provided to the students.


dot References:

Mikhail, E.M. and Gracie, G., Analysis and Adjustment of Survey Measurements,@ Van Nostrand Reinhold Co., 1981.

Strang, G. and Borre, K., ALinear Algebra, Geodesy, and GPS,@ Wellesley-Cambridge Press, 1997

Allan, A.L., AMaths for Map Makers,@ Whittles Publishing, 1997.

Brown, R.G. and Hwang, P.Y.C., AIntroduction to Random Signals and Applied Kalman Filtering,@ Third Edition, John Wiley & Sons, 1997.

Introductory books on probability, statistics, random processes, multi-variate methods, etc.