MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641050002 A) filed by Srm Institute Of Science And Technology; Rupashree; Sravani M; and Varnika P, Chennai, Tamil Nadu, on April 20, for 'high-throughput density-based spatial clustering device for autonomous signal hit identification and noise suppression.'
Inventor(s) include Rupashree; Sravani M; and Varnika P.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "This autonomous signal processing breakthrough is about efficiently processing potentially data-rich signals in a data-rich environment. It allows the processing of signal data in a pipeline hardware structure as opposed to using the conventional software-based systems. Processing starts with a signal acquisition system, which captures external signals, refines the signal through the signal processing chain, and digitizes the signal for further signal processing. The key feature of this system is the highly parallel processing of the signals in a manner able to perform density mapping and spatial clustering. Most systems rely on clustering algorithms that assume the signals being processed should be of a single defined density. This system does not require a priori knowledge of the density of the signals being processed. This is made possible with the use of signal processing algorithms in conjunction with the signal processing system's capability of real-time noise suppression and the suppression of stochastic outliers, leading to the reduced false positive rate of the external signals. The system contains a system of active cooling to maintain the optimal operating conditions. Real-time processing output is coupled with a high-bandwidth processing output interface to allow the processed data to be exported as the results of the signal processing algorithms and be integrated to other systems as the processed data. This device is ideal to use in radar and sub-systems of autonomous vehicles and systems. It allows the identification of signals of interest in highly populated or high noise environments and enables the mapping of the environment."
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