Author(s): Lukas Vojtech
Journal: Advances in Electrical and Electronic Engineering
ISSN 1804-3119
Volume: 8;
Issue: 5;
Start page: 111;
Date: 2010;
Original page
Keywords: Denoising | neural network | RFID.
ABSTRACT
Radio Frequency Identification signal denoising can be a perspective method for the future intelligent Radio Frequency Identification readers with high reading distances capability. This paper deals with the Group Method of Data Handling neural network denoising filter experiments. Capability of the probability learning of the Group Method of Data Handling filters is an effective instrument in more exacting applications in comparison with classical Finite Impulse Response filters. Results show that the realized experiment can be a perspective method for Radio Frequency Identification signal processing.
Journal: Advances in Electrical and Electronic Engineering
ISSN 1804-3119
Volume: 8;
Issue: 5;
Start page: 111;
Date: 2010;
Original page
Keywords: Denoising | neural network | RFID.
ABSTRACT
Radio Frequency Identification signal denoising can be a perspective method for the future intelligent Radio Frequency Identification readers with high reading distances capability. This paper deals with the Group Method of Data Handling neural network denoising filter experiments. Capability of the probability learning of the Group Method of Data Handling filters is an effective instrument in more exacting applications in comparison with classical Finite Impulse Response filters. Results show that the realized experiment can be a perspective method for Radio Frequency Identification signal processing.
