Classification of modality in self mixing signals using artificial intelligence techniques
Suleman Ata (18126)
Classification of modality in self mixing signals using artificial intelligence techniques - Islamabad (unpublished) 2018 - xi, 54 p. : ill. ; 30 cm. +CD
Submitted in fulfillment of the requirements for the degree of Master of Master of Sciences in Electrical Engineering to the Faculty of Engineering and Applied Sciences. Includes bibliographical references Thesis supervisor: Dr. Tassadaq Hussain
Thesis (MS)--Riphah International University, 2018
English
Artificial intelligence--Self making signals--Machine learning algorithms --Self mixing interferometry--Neural networks--FEAS
001.535 / SUL
Classification of modality in self mixing signals using artificial intelligence techniques - Islamabad (unpublished) 2018 - xi, 54 p. : ill. ; 30 cm. +CD
Submitted in fulfillment of the requirements for the degree of Master of Master of Sciences in Electrical Engineering to the Faculty of Engineering and Applied Sciences. Includes bibliographical references Thesis supervisor: Dr. Tassadaq Hussain
Thesis (MS)--Riphah International University, 2018
English
Artificial intelligence--Self making signals--Machine learning algorithms --Self mixing interferometry--Neural networks--FEAS
001.535 / SUL