Body: <p>I have used a FFNN and <a href="https://en.wikipedia.org/wiki/Liquid_state_machine" rel="nofollow noreferrer">LSM</a> to perform the same task, namely, to predict the sentence "How are you". The LSM gave me more accurate results than FFNN. However, the LSM did not produce perfect prediction and there are missing letters. More specifically, LSM produced "Hw are yo" and the FFNN predicted "Hnw brf ypu".</p>
  
  <p>What is the difference between a FFNN and a LSM, in terms of architecture and purpose?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-05-01T00:03:26.457Z
Comments.Text: What did you use to implement the LSM? Just curious. I’ve never used one.
Comments.UserDisplayName: Hanzy
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-05-01T22:29:21.297Z
Comments.Text: I believe I used tensorflow.js. @Hanzy
Comments.UserDisplayName: FreezePhoenix
Tags: <neural-networks><prediction><comparison><feedforward-neural-networks><liquid-state-machine>
Title: What is the difference between a feed-forward neural network and a liquid state machine?
UserDisplayName: FreezePhoenix
ThreadText: # What is the difference between a feed-forward neural network and a liquid state machine?
  
  (Asked by: username_0 on 2018-04-13)
  
  I have used a FFNN and [LSM](https://en.wikipedia.org/wiki/Liquid_state_machine) to perform the same task, namely, to predict the sentence "How are you". The LSM gave me more accurate results than FFNN. However, the LSM did not produce perfect prediction and there are missing letters. More specifically, LSM produced "Hw are yo" and the FFNN predicted "Hnw brf ypu".
  
  What is the difference between a FFNN and a LSM, in terms of architecture and purpose?
  
  **Tags:** neural-networks, prediction, comparison, feedforward-neural-networks, liquid-state-machine
  
  > **Comments:**
  > **username_1**: What did you use to implement the LSM? Just curious. I’ve never used one.  
  > **username_0**: I believe I used tensorflow.js. @username_1  
  
  ---
  
  ## 0 answers
  
  