dc.contributor.author |
Begum, Shaista |
|
dc.date.accessioned |
2024-09-24T05:16:22Z |
|
dc.date.available |
2024-09-24T05:16:22Z |
|
dc.date.issued |
2024-09-23 |
|
dc.identifier.uri |
http://10.250.8.41:8080/xmlui/handle/123456789/46781 |
|
dc.description |
Master of Philosophy in Mathematics
School of Natural Sciences
(Registration No: 00000403076) |
en_US |
dc.description.abstract |
In thisothesis, Firstowe presentiainewoform of iterative technique. This new itera
tiveostrategy forocontraction mappingooutperforms previousomethods suchoas Picard,
Thakur etoal.,iand Asghar Rahimi and many more. We compared these iterative meth
ods againstoa new iterative strategy and presented the findingsographically.iThe re
search investigatesothe convergence of this new iteration to the fixed point inouniformly
convexoBanachospaces using GarciaoFalset operator and worked on itsostability. We
also present the working of this iterative technique on to a boundaryivalue problem
to support our findings. Moreover, exhibit the applicabilityiof four-stepiiteration pro
cess in the delayidifferential equations. Finally, we design a training problem for an
implicitineural network that can be considered as an extension of traditional Feed
forwardinetwork. |
en_US |
dc.description.sponsorship |
Supervisor: Prof. Dr. Quanita Kiran |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
School of Natural Sciences National University of Sciences and Technology |
en_US |
dc.title |
Four Step F-Stable Iterative Technique for Garcia-Falset Mapping with Improved Convergence and Various Applications |
en_US |
dc.type |
Thesis |
en_US |