Why do sigmoid functions work in Neural Nets?

Click For Summary
SUMMARY

Sigmoid functions are integral to the functioning of Backpropagation (BP) neural networks due to their ability to map any input to a value between 0 and 1, facilitating gradient descent optimization. The mathematical properties of sigmoid functions, including their smooth gradient and non-linear characteristics, enable neural networks to approximate complex data distributions effectively. Understanding these properties is crucial for anyone delving into neural network training and optimization.

PREREQUISITES
  • Understanding of Backpropagation (BP) algorithm
  • Familiarity with neural network architecture
  • Basic knowledge of gradient descent optimization
  • Mathematical concepts related to non-linear functions
NEXT STEPS
  • Research the mathematical properties of sigmoid functions in neural networks
  • Explore alternative activation functions such as ReLU and their advantages
  • Learn about the impact of activation functions on training convergence
  • Study the role of gradient descent in optimizing neural network performance
USEFUL FOR

Individuals interested in machine learning, particularly those focused on neural network development, optimization, and mathematical foundations of activation functions.

apj_anshul
Messages
5
Reaction score
0
Hi,

I have just started programming for Neural networks. I am currently working on understanding how a Backpropogation (BP) neural net works. While the algorithm for training in BP nets is quite straightforward, I was unable to find any text on why the algorithm works. More specifically, I am looking for some mathematical reasoning to justify using sigmoid functions in neural nets, and what makes them mimic almost any data distribution thrown at them.

Thanks!
 
Technology news on Phys.org

Similar threads

Why is my multilayered, feedforward neural network not working?
  • · Replies 50 ·
2
Replies
50
Views
4K
Normalization condition with a neural network
  • · Replies 3 ·
Replies
3
Views
1K
Neural Nets in AI: What's the Intelligent Part?
  • · Replies 19 ·
Replies
19
Views
3K
Use of AI (ML/DL) in Science
  • · Replies 6 ·
Replies
6
Views
1K
Python Building a homemade Long Short Term Memory with FSMs
  • · Replies 2 ·
Replies
2
Views
3K
Thoughts on neural networks "discovering" physical concepts
  • · Replies 1 ·
Replies
1
Views
2K
How should a physicist learn Machine Learning?
  • · Replies 5 ·
Replies
5
Views
2K
Debugging a Backprop Neural Network: Issues & Solutions
  • · Replies 3 ·
Replies
3
Views
2K
Looking for physics based simulation for data generation
  • · Replies 6 ·
Replies
6
Views
2K
Python Help solving a geometrical matching issue with Graph Neural Networks
  • · Replies 1 ·
Replies
1
Views
2K