Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The use of time-frequency distributions is proposed as a nonlinear signal processing technique that is combined with a pattern recognition approach to identify superimposed transmission modes in a reconfigurable wireless terminal based on software-defined radio techniques. In particular, a software-defined radio receiver is described aiming at the identification of two coexistent communication modes: frequency hopping code division multiple access and direct sequence code division multiple access. As a case study, two standards, based on the previous modes and operating in the same band (industrial, scientific, and medical), are considered: IEEE WLAN 802.11b (direct sequence) and Bluetooth (frequency hopping). Neural classifiers are used to obtain identification results. A comparison beten two different neural classifiers is made in terms of relative error frequency.
['Matteo Gandetto', 'Marco Guainazzo', 'Carlo S. Regazzoni']
I am writing a research paper on a idea Use of time-frequency analysis and neural networks for mode identification in a wireless software-defined radio approach
[{"from": "human", "value": "I am writing a research paper on a idea Use of time-frequency analysis and neural networks for mode identification in a wireless software-defined radio approach"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The use of time-frequency distributions is proposed as a nonlinear signal processing technique that is combined with a pattern recognition approach to identify superimposed transmission modes in a reconfigurable wireless terminal based on software-defined radio techniques. In particular, a software-defined radio receiver is described aiming at the identification of two coexistent communication modes: frequency hopping code division multiple access and direct sequence code division multiple access. As a case study, two standards, based on the previous modes and operating in the same band (industrial, scientific, and medical), are considered: IEEE WLAN 802.11b (direct sequence) and Bluetooth (frequency hopping). Neural classifiers are used to obtain identification results. A comparison beten two different neural classifiers is made in terms of relative error frequency."}]