"A symmetric linear neural network that learns principal components and ..."

Ferdinand Peper, Hideki Noda (1996)

> Home

Details and statistics

DOI: 10.1109/72.508948

access: closed

type: Journal Article

metadata version: 2018-11-14

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - journals/tnn/PeperN96
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/tnn/PeperN96
Ferdinand Peper, Hideki Noda:
A symmetric linear neural network that learns principal components and their variances. IEEE Trans. Neural Networks 7(4): 1042-1047 (1996)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.