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In this paper, we describe a simplified spiking neuron architecture optimized for embedded systems implementation, proving the learning capabilities of the design.
The inherent capabilities of the design in handling short data records and low-frequency signals allow its applications to a wide class of problems.
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The capabilities of the designed method were tested in the prediction of the glass point of another 100 ionic liquids not used in the correlation step.
In order to test the capabilities of the designed system, impedometric and voltammetric measurements were carried out on five different commercial cola drinks (brands I V).
Though the testing is real-world data based, in order to expose a tangible aim and capabilities of the designed tool, the testing scenarios are constructed in such a way to reflect specific borderline operational situations, while emphasizing occurring conflicting decision key criteria.
The error correction capability of the design is investigated as well.
The plots provide a comprehensive assessment of the overall prediction capability of the design within the region R.
Subsequently, the system was used to acquire and process real GPS data to demonstrate the capability of the design.
In this study we will show the capability of the design of a LAS alumina submicron composite.
The capability of the design is implemented in an open source main-memory database system H2 and evaluated by realistic workloads of RFID applications.
For datasets I – III, we performed our SWISS permutation test on the full gene set to test whether there was a significant difference in the clustering capabilities of the reference design versus the single channel design.
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