Object detection is a common and challenging problem in today's world. Also due to the rapid development of deep learning employing underlying deep models over the past ten years, many researchers have investigate...
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The proposed BIST architecture focuses on minimizing power consumption during the testing phase while maintaining high fault coverage. It leverages the capabilities of the Verilog hardware description language to mode...
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Signal acquisition system is widely used in various fields of reality, due to the data acquisition rate and processor performance enhancement as well as the development of sensor arrays and other technologies, the dat...
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Weather radar simulation technology has many applications in civil aviation, military and other fields. Using the emulator, weather radar signals from the past can be observed repeatedly. With the development of elect...
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Industrial control systems (ICS) are required to be designed and operated safely even when subjected to cyberattacks. Fallback control is necessary for the safe operation of ICS. One of fallback control systems is a r...
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In this paper a novel design of a low power based 3:8 decoder circuit is proposed for high speed operations. Decoders having great application usage in the field of Address Decoding for Memory devices, Control logic f...
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While analyzing radar signals, the constant false alarm rate (CFAR) method is crucial for detecting targets. Target detection has to be very accurate, particularly in nonhomogeneous situations like multi-target or clu...
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To optimize manufacturing processes and ensure environmental compliance, careful management of humidity and carbon dioxide levels is crucial in industrial contexts. The creation and deployment of a monitoring and cont...
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Sample Entropy (SampEn) is an information entropy algorithm widely used for complexity analysis and chaos estimation in many applications. In particular, SampEn measures complexity of time series by the conditional pr...
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ISBN:
(数字)9781665453363
ISBN:
(纸本)9781665453363
Sample Entropy (SampEn) is an information entropy algorithm widely used for complexity analysis and chaos estimation in many applications. In particular, SampEn measures complexity of time series by the conditional probability of the inner pattern. Unfortunately, the straightforward implementation of SampEn is quadratic time complexity, restricting its realtime analysis ability for health applications and long-term data analysis. Although researchers have proposed fast versions of SampEn to avoid unnecessary comparisons, they have not been accelerated yet due to their performance bottleneck in the complex similarity pair process. In this paper, we evaluate fast SampEn algorithms by employing multi-source biomedical signals on an field-programmable Gate Arrays (FPGA). Since fast SampEn algorithms based of a pre-sorting stage promise to outperform other SampEn algorithms, Lightweight SampEn based on Merge Sort is here implemented and optimized. Different type of optimizations, that can be generalized for similar Lightweight-based SampEn algorithms, are used to reduce the overall latency while the data throughput is increased. A load balancing strategy for multi similarity pair modules is also proposed to solve the unbalancing loads, a bottleneck when increasing the execution parallelism of this type of algorithms. As a result, the proposed SampEn architecture runs 10 times faster than the fastest SampEn implementation on a modern CPU.
Currently, programming sequences for pneumatic industrial processes are carried out using different methods: pneumatic programming (in disuse), electro pneumatic (using electrical contactors) and programming with a PL...
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ISBN:
(数字)9798331509231
ISBN:
(纸本)9798331509248
Currently, programming sequences for pneumatic industrial processes are carried out using different methods: pneumatic programming (in disuse), electro pneumatic (using electrical contactors) and programming with a PLC (programmablelogic Controller). Among these, programming using Ladder logic is the most commonly used and widely recognized for PLC devices. However, its implementation might take large periods of time, becoming a tedious task and increasing its level of complexity as a function of the number of cylinders, movements and phases that the process requires. This work develops and implements a control algorithm in the LabView graphical environment, which is subsequently connected to a Siemens PLC via an NI OPC (National Instruments OLE for Process Control) Server. The control algorithm is experimentally tested and proven successful in various scenarios of industrial pneumatic sequences.
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