Using neural networks with a linear output neuron to model plasma etch processes

IEEE International Symposium on Industrial Electronics

Volumn 1, Issue , 2001, Pages 441-445

  Kim, B ^a   Choi, W ^a   Kim, H ^a  

^a Sejong University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; GRADIENT METHODS; LINEARIZATION; NEURAL NETWORKS; OPTIMIZATION; PLASMA ETCHING; SEMICONDUCTOR DEVICE MODELS;

BACKPROPAGATION NEURAL NETWORK; LINEAR OUTPUT NEURON; MAGNETICALLY ENHANCED REACTIVE ION ETCH; PLASMA ETCH PROCESS;

INDUSTRIAL ELECTRONICS;

EID: 0034845425     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Two-dimensional hybrid model of inductively coupled plasma sources for etching
2. Two-dimensional fluid model of high density inductively coupled plasma sources
3. Advantages of plasma etch modeling using neural networks over statistical techniques
4. Use of neural networks in modeling semiconductor manufacturing processes: An exmaple of plasma etch modeling
5. Reactive ion etch modeling using neural networks and simulated annealing
6. 4 inductively coupled plasma
7. 6 plasma
8. Learning representations by back-propagation error
9. An optimal neural network process model for plasma etching
10. An optimal neural network plasma model: A case study