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This would then be synthesized into digital logic hardware for implementation on devices such as FPGAs (Field Programmable Gate Arrays) and ASICs (Application Specific Integrated Circuits).
However, there may be significant technical barriers to implementing this type of approach including tube blockage and miniaturization of the chemical analysis hardware for implementation in an implantable device.
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In this paper, we present a simplified multicore based scalable hardware architecture for implementation of k-means.
In this paper a high-speed hardware structure for implementation of Itoh-Tsujii Inversion Algorithm (ITA) based on Gaussian normal basis hybrid-double multiplier is presented.
The prices for the hardware for the implementations range from US$495 to US$717.
The proposed algorithm with its improved SIR using harmonic alignment and efficient computational complexity is suitable for hardware implementation for the real-time blind source separation of speech signals.
Then, we compare its performance in terms of accuracy and hardware resources needed for implementation.
Figure 6 Hardware architecture adopted for implementation of the PPI algorithm.
Since only the real solutions can be accepted for hardware implementation, we are looking for exclusively these roots.
The contribution presented in this paper is a metric-based approach for estimating the time needed for hardware implementation in relation to the complexity of an algorithm.
To solve the high computational complexity problem, Hong et al. [10] proposed a new update model for the particle PHD filter that is suitable for hardware implementation.
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