國立臺北科技大學電機系首頁 本校防疫資訊專區(將開啟新視窗) 歡迎加入台北科大電機系臉書粉絲專頁(將開啟新視窗)
站內搜尋 | 設定為藍色網頁 設定為橘色網頁 設定為綠色網頁 設定為紫色網頁 設定為灰色網頁 放大網頁 | 網站導覽 | 回首頁 | English
:::快速選單  訪客身份考生身份學生身份教職身份系友身份考古題 ::: 快速鍵 | 行事曆 | 緊急聯絡電話 | 臉書粉絲專頁
:::首頁 > 課程資訊 > 課程概述 > 模型辨認
::: 模型辨認 3學分
3小時
課程名稱 模型辨認
英文課程名稱 Pattern Recognition
中文課程概要 1. 類神經網路簡介2. 層狀認知網路3. 競爭學習神經網路4. 適應共振理論5. 聯想記憶6. 特徵萃取
英文課程概要 Topics that are covered in the course include: " Bayesian decision theory: the theoretical statistical basis for recognition based on Bayes theorem from probability " Maximum-likelihood and Bayesian parameter estimation: parameters of probability density functions " Nonparametric techniques: Parzen window, k-nearest neighbor " Linear discriminant functions: gradient descent, relaxation, minimum squared-error procedures such as LMS, and support vector machines " Algorithm-independent machine learning " Unsupervised learning and clustering The course is quite mathematical. Students enrolling this class are expected to have a good understanding of probability and random variables, both one-dimensional and multi-dimensional, and a good background in linear algebra as well as calculus. Some of the necessary math will be reviewed at the beginning of the course, but it is only a quick review, not a math course. Grades will be based on homework, tests, and small computer projects.
:::
10608台北市忠孝東路三段1號 電話:(02)27712171 #2100 傳真:(02)27317187
Copyright © 2024 國立臺北科技大學電機工程系 All Rights Reserved.
如對網頁內容有任何建議,請與我們聯絡
2136700 Visits
since May 26, 2003.