Math 322 Computation and Optimization 2 - Revision history

Ls5: Replaced content with "{{db-g7}}"

2013-04-03T22:19:18Z

Replaced content with "{{db-g7}}"

Ls5 at 21:58, 3 April 2013

2013-04-03T21:58:30Z

Ls5 at 22:05, 1 April 2013

2013-04-01T22:05:15Z

Ls5: Created page with "== Catalog Information == === Title === Computation and Optimization 2 === (Credit Hours:Lecture Hours:Lab Hours) === (3:3:0) === Offered === W === Prerequisite === [[Math 32..."

2013-04-01T22:04:45Z

Created page with "== Catalog Information == === Title === Computation and Optimization 2 === (Credit Hours:Lecture Hours:Lab Hours) === (3:3:0) === Offered === W === Prerequisite === [[Math 32..."

New page

== Catalog Information ==

=== Title ===
Computation and Optimization 2

=== (Credit Hours:Lecture Hours:Lab Hours) ===
(3:3:0)

=== Offered ===
W

=== Prerequisite ===
[[Math 320 Computation and Optimization 1|Math 320]]; concurrent with [[Math 346]], [[Math 323]]

=== Description ===
Algorithms used to solve dynamic programming problems and advanced computing problems. Topics include finite-horizon and infinite-horizon dynamic programming, discrete transforms, compressed sensing, heuristics, branch and bound, conditioning and stability.

== Desired Learning Outcomes ==

=== Prerequisites ===
[[Math 320 Computation and Optimization 1|320]]; concurrent with [[Math 346]], [[Math 323]]

=== Minimal learning outcomes ===
Students will have a solid understanding of the concepts listed below. They will be able to prove many of the theorems that are central to this material. They will understand the model specifications for the algorithms, and be able to recognize whether they apply in the context of a given application or not. They will be able to perform the relevant computations on small, simple problems. They will be able to describe the algorithms well enough that they could program simple versions of them, and will have a basic knowledge of the computational strengths and weaknesses of the algorithms covered.

# Dynamic Programming
#* Finite-Horizon Problems
#*Infinite-Horizon Problems
#*Uncertain Stopping Times
#*Value and Policy Iteration
#*Numerical Techniques
#*Applications
#Discrete Transforms
#*z-Transforms
#* Discrete Cosine Transform
#*Fast Fourier Transform (FFT) (including convolutions)
#*Shannon-Nyquist Theorem, including Gibbs Phenomenon
#*Discrete Wavelet Transforms
# Advanced Algorithms
#*Compressed Sensing
#*Heuristics, Branch and Bound
# Conditioning and Stability
#*Conditioning
#*Forward Stability
#*Backward Stability

=== Textbooks ===
Possible textbooks for this course include (but are not limited to):

*

=== Additional topics ===

=== Courses for which this course is prerequisite ===

[[Category:Courses|322]]

← Older revision		Revision as of 22:19, 3 April 2013
Line 1:		Line 1:
	{{db-g7}}		{{db-g7}}
−	~~== Catalog Information ==~~
−
−	~~=== Title ===~~
−	~~Computation and Optimization 2~~
−
−	~~=== (Credit Hours:Lecture Hours:Lab Hours) ===~~
−	~~(3:3:0)~~
−
−	~~=== Offered ===~~
−	W
−
−	~~=== Prerequisite ===~~
−	~~[[Math 320 Computation and Optimization 1\|Math 320]]; concurrent with [[Math 346]], [[Math 323]]~~
−
−	~~=== Description ===~~
−	Algorithms used to solve dynamic programming problems and advanced computing problems. Topics include finite-horizon and infinite-horizon dynamic programming, discrete transforms, compressed sensing, heuristics, branch and bound, conditioning and stability.
−
−	~~== Desired Learning Outcomes ==~~
−
−	~~=== Prerequisites ===~~
−	~~[[Math 320 Computation and Optimization 1\|Math 320]]; concurrent with [[Math 346]], [[Math 323]]~~
−
−	~~=== Minimal learning outcomes ===~~
−	Students will have a solid understanding of the concepts listed below. They will be able to prove many of the theorems that are central to this material. They will understand the model specifications for the algorithms, and be able to recognize whether they apply in the context of a given application or not. They will be able to perform the relevant computations on small, simple problems. They will be able to describe the algorithms well enough that they could program simple versions of them, and will have a basic knowledge of the computational strengths and weaknesses of the algorithms covered.
−
−	~~# Dynamic Programming~~
−	~~#* Finite-Horizon Problems~~
−	~~#*Infinite-Horizon Problems~~
−	~~#*Uncertain Stopping Times~~
−	~~#*Value and Policy Iteration~~
−	~~#*Numerical Techniques~~
−	~~#*Applications~~
−	~~#Discrete Transforms~~
−	~~#*z-Transforms~~
−	~~#* Discrete Cosine Transform~~
−	~~#*Fast Fourier Transform (FFT) (including convolutions)~~
−	~~#*Shannon-Nyquist Theorem, including Gibbs Phenomenon~~
−	~~#*Discrete Wavelet Transforms~~
−	~~# Advanced Algorithms~~
−	~~#*Compressed Sensing~~
−	~~#*Heuristics, Branch and Bound~~
−	~~# Conditioning and Stability~~
−	~~#*Conditioning~~
−	~~#*Forward Stability~~
−	~~#*Backward Stability~~
−
−	~~=== Textbooks ===~~
−	~~Possible textbooks for this course include (but are not limited to):~~
−
−	*
−
−	~~=== Additional topics ===~~
−
−	~~=== Courses for which this course is prerequisite ===~~
−
−	~~[[Category:Courses\|322]]~~

← Older revision		Revision as of 21:58, 3 April 2013
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		+	{{db-g7}}
	== Catalog Information ==		== Catalog Information ==

@@ Line 19: / Line 19: @@
 === Prerequisites ===
-[[Math 320 Computation and Optimization 1|320]]; concurrent with [[Math 346]], [[Math 323]]
+[[Math 320 Computation and Optimization 1|Math 320]]; concurrent with [[Math 346]], [[Math 323]]
 === Minimal learning outcomes ===