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There are also a number of device-specific dimensions that are critical to keep in mind which drive position determination implementation on device.
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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).
In this paper we present the Sum of Absolute Difference algorithm (SAD) implementation on FPGA device.
In this case, dedicated hardware and its potential on-chip implementation on FPGA devices become an efficient solution.
This paper presents the design of high speed parallel architectures for convolutional encoders and its implementation on FPGA devices.
Such an array architecture is easily scalable to handle images of different sizes and is suitable for implementation on reconfigurable devices like FPGAs.
As a huge range of embedded applications is deployed on Field Programmable Gate Arrays (FPGAs) devices, most widespread PUFs' architectures are based on Ring Oscillators (ROs), as they are suitable for an implementation on programmable devices.
In this manner, MOFs' performance have been improved in certain applications by choosing the optimal particle morphology and dimensions that enhance the materials' properties and/or facilitate their implementation on functional devices.
For the development process, we set up a methodology and a CAD tool chain that span the entire design process from initial specification in a high-level language to implementation on FPGA devices.
However, backprojection contains a high degree of parallelism, which makes it suitable for the implementation on reconfigurable devices.
The next section discusses our implementation on constrained devices, followed by section 6 presenting a detailed experimental and mathematical evaluation.
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