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And here the review goes: | And here the review goes: | ||
| + | This slecture discussed the concept of Bayes parameter estimation (BPE). | ||
| + | *First it gives the definition of BPE. | ||
| + | *Then it talks about using BPE to solve daily problem and get the conclusion that the Bayes estimator is based on cumulative information or knowledge of unknown parameters, from past and present. The example given in this lecture is illustrative, which could help reader better understand this concept. | ||
| + | *Then the author gives an example of continuous case using Gaussian random variable. | ||
| + | Overall speaking, this slecture is well written and interesting. But there are still minor thing that could be improved, like the presentation. For example, the tpyeface of "Figure 8" is different from the others, and even though, we could understand which one is subplot (a) for Figure 8, but it still good to have subtitle (a) and (b) below each of the subplot. | ||
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Revision as of 12:04, 30 April 2014
Comments of slecture: Bayes Parameter Estimation (BPE)
A slecture by ECE student Haiguang Wen
Partially based on the ECE662 lecture material of Prof. Mireille Boutin.
This is the talk page for the sLecture notes on Bayes Parameter Estimation (BPE) tutorial. Please leave me a comment below if you have any questions, if you notice any errors or if you would like to discuss a topic further.
Questions and Comments
This slecture will be reviewed by Weibao Wang.
And here the review goes:
This slecture discussed the concept of Bayes parameter estimation (BPE).
- First it gives the definition of BPE.
- Then it talks about using BPE to solve daily problem and get the conclusion that the Bayes estimator is based on cumulative information or knowledge of unknown parameters, from past and present. The example given in this lecture is illustrative, which could help reader better understand this concept.
- Then the author gives an example of continuous case using Gaussian random variable.
Overall speaking, this slecture is well written and interesting. But there are still minor thing that could be improved, like the presentation. For example, the tpyeface of "Figure 8" is different from the others, and even though, we could understand which one is subplot (a) for Figure 8, but it still good to have subtitle (a) and (b) below each of the subplot.
