Re: advise on math course

taati_at_dpir.com
Date: 01/17/05 

Date: 17 Jan 2005 06:55:20 -0800

> Linear and Nonlinear Equations, Linear Least Squares, Eigenvalue
> Problems, Optimization, Interpolation, Initial and Boundary Value
> Problems for ODEs,Fast Fourier Transform

NOT recommended! This perhaps would be tiresome, unless you have a
specific problem in mind, or any special reason you want to learn the
techniques. On the other hand it can come quite useful depending on
your future job, mainly if you are going to work with engineers.

> And the other one is Stochastic Models
> reliability, probability, queuing theory, inventory systems, Markov
> chain models, Markov decision processes, discrete-event simulation

Again, it can come quite useful, with wide range of application. This
one is perhaps more interesting.

> If one has taken such similar courses please let me know how these
> courses helped and what typical research is being done in these
areas.

I haven't had any work experience on these, but I can reckon how it can
be. The first one comes handy when you have your problem (almost)
formulated. Say, an engineer comes to you and ask you to write a
program to solve his optimization problem. You should find a reliable
method to give good answers in practice.

On the other hand, the second one also involves some modeling. You
will have to interact with engineers/computer
scientists/biologists/economists/... to first create a suitable model,
then analyze it either by mathematical tools or by simulation. Say,
you will have to create a model of the network, and find the
specification of the server.

Siamak

Relevant Pages

  • Re: Gaussian elimination with guaranteed positive coefficients
    ... It seems that linear optimization is exactly ... If your functions W, etc, are linear, this is a classical linear ... coefficients must be positive values and the sum of all coefficients ... different light bulbs, and have only one light bulb on at a time. ...
    (sci.math.num-analysis)
  • Re: Quadratic Optimization Problem
    ... Since my problem is a nonlinear convex ... The problem where constraints are linear and the objective function is ... algorithm for nonlinearly constrained optimization. ...
    (comp.lang.python)
  • Re: Optimization and random errors
    ... However those algorithms assume the ideal accuracy of the result. ... If you are using input-squared rules as your cost function, if the output is a linear combination of the inputs, and if the noise really is Gaussian then there are some fairly direct optimizing techniques available from linear control theory which I think apply. ... If any of the conditions I state above aren't true then chances are your optimal solution is not a linear one, and the optimization process will be a long and difficult one that is quite likely immune to exact solutions. ...
    (comp.dsp)
  • Re: Optimization and random errors
    ... function has random gaussian error. ... output is a linear combination of the inputs, and if the noise really is Gaussian then there are some fairly direct optimizing techniques available from linear control theory which I think apply. ... Look in a graduate-level linear control book such as "Linear Systems" by Kailath. ... In that case you'll want to dive into linear programming and general optimization. ...
    (comp.dsp)
  • Re: SW World opinions
    ... good luck in your mission ... I find engineers typically have real trouble with id people because they are ... quite uncomfortable in themselves about things outside the linear, ...
    (comp.cad.solidworks)