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块稀疏贝叶斯重构算法

于 2020-12-06 发布
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基于块稀疏信号的重构算法。稀疏贝叶斯学习算法。

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However, using other settings than those recommended mightINSTRUMENTSPage 5 of 19SWRA308Aresult in suboptimal performance in areas like current consumption, EVM, and spuriousemissionTc=25C, Vdd=3.0V, f=2440 MHz if nothing else is stated All parameters are measuredon the CC2530-CC2591EM reference design with a 50 32 load2221-2V201918171611121314151617181920212223242526251510OxE5OxC5OxA50X850x65540-30-20-1001020304050607080ISTRUMENTSPage 6 of 19SWRA308A98Avg 3.6VAva 3vAvg 2V110111213141516171819202122232425261023.6V-1062V-110-40-30-20-100102030405060708070604020-Wanted signal at:-82 dBm10ISTRUMENTSPage 7 of 19SWRA308ACC2530-CC2591EM High Gain ModeC C2530-CC2591EM Low Gain Mode- CC2530EM40000-100110100908070-60-50-40-30-20-100The IEEE standard 802.15. 4 [8] requires the transmitted spectral power to be less than thelimits specified in table 4.7If-fc>3.5 MHz-20 dB-30 dBmThe results below are given for Tc=25 C, Vdd=3.0V and f= 2440 MHz, and are measuredon the CC2530-CC259 1EM reference design with a 50 Q loadIEEE absoluteChannel 182432.52435243752442524452447.5ISTRUMENTSPage 8 of 19SWRA308AOnly a few external components are required for the CC2530-CC2591 reference design. 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