Showing 1 - 20 results of 126 for search '"chipset"', query time: 0.08s Refine Results
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    A Ku-Band GaAs Multifunction Transmitter and Receiver Chipset by Hyunkyu Lee, Younghwan Kim, Iljin Lee, Dongkyo Kim, Kwangwon Park, Sanggeun Jeon

    Published 2020-08-01
    “…This paper presents a Ku-band monolithic multifunction transmitter and receiver chipset fabricated in 0.25-μm GaAs pseudomorphic high-electron mobility transistor technology. …”
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    Article
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    Software develpment for sensor integration with TV whitespace based chipset by Pushkarna Rajat

    Published 2020
    “…The work presented here focuses on developing software for sensor integration of a TV whitespace-based chipset for IoT applications. The major advantage of such a device is that it utilizes the unlicensed spectrum of TV band thereby it is also a source of free WiFi. …”
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    Thesis-Master by Coursework
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    Software development for sensor integration with TV whitespace based chipset by Pushkarna, Rajat

    Published 2021
    “…The work presented here focuses on developing software for sensor integration of a TV whitespace-based chipset for IoT applications. The major advantage of such a device is that it utilizes the unlicensed spectrum of TV band thereby it is also a source of free WiFi. …”
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    Thesis-Master by Coursework
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    A 39 GHz Dual-Channel Transceiver Chipset with an Advanced LTCC Package for 5G Multi-Beam MIMO Systems by Yiming Yu, Zhilin Chen, Chenxi Zhao, Huihua Liu, Yunqiu Wu, Wen-Yan Yin, Kai Kang

    Published 2023-03-01
    “…This article presents a 39 GHz transceiver front-end chipset for 5G multi-input multi-output (MIMO) applications. …”
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    Article
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    A Portable Spectrometric System for Quantitative Prediction of the Soluble Solids Content of Apples with a Pre-calibrated Multispectral Sensor Chipset by Nhut-Thanh Tran, Masayuki Fukuzawa

    Published 2020-10-01
    “…In the proposed system, the spectra of apples were collected by a simple optical setup with a cheap pre-calibrated multispectral chipset. An optimal multiple linear regression model with five wavebands at 900, 760, 730, 680, and 535 nm revealed the best performance with the coefficient of determination of prediction and the root mean square error of prediction of 0.861 and 0.403 °Brix, respectively, which was comparable to that of the previous studies using dispersive spectrometers. …”
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    Article
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