Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Uday Wali"'
Autor:
Bahubali K. Shiragapur, Uday Wali
Publikováno v:
ICTACT Journal on Communication Technology, Vol 7, Iss 1, Pp 1229-1234 (2016)
In this article, the research work investigated is based on an error correction coding techniques are used to reduce the undesirable Peak-to-Average Power Ratio (PAPR) quantity. The Golay Code (24, 12), Reed-Muller code (16, 11), Hamming code (7, 4)
Externí odkaz:
https://doaj.org/article/d6211629d1ca4dd284bb3b077d94ab03
Autor:
Shilpa Mayannavar, Uday Wali
Publikováno v:
Emerging Research in Computing, Information, Communication and Applications ISBN: 9789811954818
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7edbc84f8ab8a7a4688ea0fe64d78f6e
https://doi.org/10.1007/978-981-19-5482-5_51
https://doi.org/10.1007/978-981-19-5482-5_51
Publikováno v:
Machine Learning for Predictive Analysis ISBN: 9789811571053
A critical component of Cognitive Radio (CR) is an ability to predict availability of unused RF slots at a given time and location. Secondary users can use such unused slots without any licensing requirements as long as they retreat when the primary
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9e598ad25a1ceb6403cdb6cd5d087b2
https://doi.org/10.1007/978-981-15-7106-0_29
https://doi.org/10.1007/978-981-15-7106-0_29
Autor:
Ashwini Desai, Uday Wali
Publikováno v:
2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT).
VLSI Floor-planning is known to be a NP hard problem. Therefore, most of the EDA tools use heuristic algorithms to solve this problem that yield near optimal solutions. Simulated annealing has been known to produce good results in floor planning. How
Autor:
Uday Wali, Uma Kulkarni
Publikováno v:
2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT).
Induction melting is a very energy intensive and dynamic process. Therefore, improving the power efficiency is critical to reduce the cost of production. Saving of just a percent of energy can reduce the power bill considerably. There are several fac
Publikováno v:
SN Applied Sciences. 2
This paper proposes a new type of Artificial Neural Network called Auto-Resonance Network (ARN) derived from synergistic control of biological joints. The network can be tuned to any real valued input without any degradation of learning rate. Neurona
Autor:
Uday Wali, Shilpa Mayannavar
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030166595
ISDA (2)
ISDA (2)
Auto Resonance Network (ARN) is a general purpose Artificial Neural Network (ANN) capable of non-linear data classification. Each node in an ARN resonates when it receives a specific set of input values. Coverage of an ARN node indicates the spread o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ad6405dcc405ff1bdfec730ed9feaf0
https://doi.org/10.1007/978-3-030-16660-1_46
https://doi.org/10.1007/978-3-030-16660-1_46
Publikováno v:
2019 International Conference on Communication and Signal Processing (ICCSP).
Classification and grading of human In-Vitro Fertilized (IVF) embryos is time consuming and challenging. Various factors like morphological and genetic quality fertilized egg, its sensitivity to environmental factors like temperature, and pH, etc mak
Autor:
Uday Wali, Shilpa Mayannavar
Publikováno v:
Communications in Computer and Information Science ISBN: 9789811513831
Auto Resonance Network (ARN) is a biologically inspired generic non-linear data classifier with controllable noise tolerance useful in control applications like robotic path planning. It appears that multi-layer ARN can be useful in image recognition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b12dbc87083f6e8cb1bb55c503b3ee0c
https://doi.org/10.1007/978-981-15-1384-8_13
https://doi.org/10.1007/978-981-15-1384-8_13
Autor:
Shilpa Mayannavar, Uday Wali
Publikováno v:
2018 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT).
Computational environment of Deep Learning Neural Networks (DLNNs) is considerably different than that of Conventional computer systems. DLNNs require thousands, if not millions of compute cores compared to one or few in conventional systems. Therefo