Implementation of adaptive filters based on neural networks for digital signal processing

Публікація:
Implementation of adaptive filters based on neural networks for digital signal processing

dc.contributor.author	Stepuro, O. V.
dc.date.accessioned	2025-04-24T08:12:05Z
dc.date.available	2025-04-24T08:12:05Z
dc.date.issued	2025
dc.description.abstract	One approach that overcomes the limitations of traditional methods is the use of multi-layer neural network architectures such as MLP and RNN. These networks can automatically learn from input signals and adjust their parameters for optimal filtering. The network consists of three main components: an input layer, one or more hidden layers, and an output layer, which allows for nonlinear transformation of the signal. The network is trained using the backpropagation algorithm, which minimizes the error between the actual and desired output.
dc.identifier.citation	Stepuro O. V. Implementation of adaptive filters based on neural networks for digital signal processing / O. V. Stepuro ; scientific supervisor sn. l. V. S. Chumak // Радіоелектроніка та молодь у XXI столітті : матеріали 29-го Міжнар. молодіж. форуму, 16–19 квітня 2025 р. – Харків : ХНУРЕ, 2025. – Т. 3. – С. 567–568.
dc.identifier.uri	https://openarchive.nure.ua/handle/document/30672
dc.language.iso	en_US
dc.publisher	ХНУРЕ
dc.subject	signal processing
dc.subject	adaptive filter
dc.title	Implementation of adaptive filters based on neural networks for digital signal processing
dc.type	Thesis
dspace.entity.type	Publication