Material Information |
| Title: |
Synaptic Neural Networks--Supervised Learning Without Weights |
| Physical Description: |
Book |
| Language: |
English |
| Creator: |
Caswell, Chris |
| Publisher: |
New College of Florida |
| Place of Publication: |
Sarasota, Fla. |
| Creation Date: |
2009 |
| Publication Date: |
2009 |
Subjects |
| Subjects / Keywords: |
Computer Science
Artificial Neural Networks
Artificial Intelligence |
| Genre: |
bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation |
Notes |
| Abstract: |
This thesis proposes a novel model of artificial neural networks wherein the notion of synaptic weights is removed and a Gaussian activation function is used. The new, sporadically-connected Neural Networksare trained by a probabilistic extension of the famous error-backpropagationalgorithm and tested using, a set of standard benchmarking rules and problem sets. Despite its simplicity, the proposed model is shown to be capable of generalizing on real-world data with a performance comparable to that of a Gaussian-activated weighted network. We then explore the possible advantages the model might have for efficient FPGA hardware implementations and the biological relevance it has with the current understanding and modeling of neuroplasticity. |
| Statement of Responsibility: |
by Chris Caswell |
| Thesis: |
Thesis (B.A.) -- New College of Florida, 2009 |
| Electronic Access: |
RESTRICTED TO NCF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE |
| Bibliography: |
Includes bibliographical references. |
| Source of Description: |
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The New College of Florida, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. |
| Local: |
Faculty Sponsor: Henckell, Karsten; McDonald, Patrick |
Record Information |
| Source Institution: |
New College of Florida |
| Holding Location: |
New College of Florida |
| Rights Management: |
Applicable rights reserved. |
| Classification: |
local - S.T. 2009 C35 |
| System ID: |
NCFE004063:00001 |
|
Material Information |
| Title: |
Synaptic Neural Networks--Supervised Learning Without Weights |
| Physical Description: |
Book |
| Language: |
English |
| Creator: |
Caswell, Chris |
| Publisher: |
New College of Florida |
| Place of Publication: |
Sarasota, Fla. |
| Creation Date: |
2009 |
| Publication Date: |
2009 |
Subjects |
| Subjects / Keywords: |
Computer Science
Artificial Neural Networks
Artificial Intelligence |
| Genre: |
bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation |
Notes |
| Abstract: |
This thesis proposes a novel model of artificial neural networks wherein the notion of synaptic weights is removed and a Gaussian activation function is used. The new, sporadically-connected Neural Networksare trained by a probabilistic extension of the famous error-backpropagationalgorithm and tested using, a set of standard benchmarking rules and problem sets. Despite its simplicity, the proposed model is shown to be capable of generalizing on real-world data with a performance comparable to that of a Gaussian-activated weighted network. We then explore the possible advantages the model might have for efficient FPGA hardware implementations and the biological relevance it has with the current understanding and modeling of neuroplasticity. |
| Statement of Responsibility: |
by Chris Caswell |
| Thesis: |
Thesis (B.A.) -- New College of Florida, 2009 |
| Electronic Access: |
RESTRICTED TO NCF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE |
| Bibliography: |
Includes bibliographical references. |
| Source of Description: |
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The New College of Florida, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. |
| Local: |
Faculty Sponsor: Henckell, Karsten; McDonald, Patrick |
Record Information |
| Source Institution: |
New College of Florida |
| Holding Location: |
New College of Florida |
| Rights Management: |
Applicable rights reserved. |
| Classification: |
local - S.T. 2009 C35 |
| System ID: |
NCFE004063:00001 |
|