A 30mV input battery-less power management system

Yap, Jim Hui; Wong, Yan Chiew

doi:10.11591/eei.v8i4.1614

Cited by 4 publications

(6 citation statements)

References 20 publications

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“…Therefore, it is important to develop the mathematical foundations ofsubband analysis and signal synthesis from the standpoint of partitioning transformation regions into subbands of other transformations using orthonormal bases. This allows for a completely regular way to implement the subband methodology in these cases, as well [17][18][19][20][21][22][23][24][25].…”

Section: Discussionmentioning

confidence: 99%

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Generalized sub band analysis and signal synthesis

Zhilyakov¹,

Белов²,

Oleinik³

et al. 2020

Bulletin EEI

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Currently, one of the main approaches used in analyzing properties and synthesis of signals in various classes is the subband methodology, which is carried out from the position of Fourier transform of signal samples (frequency representations) into subbands of the transform definition domain (transformants). In this case, the main tool, which is widely used for subband analysis (including wavelet analysis), is usage of bandpass filters (mainly those with finite impulse response or FIR filters). The present paper introduces the basics of building a theory forsubband analysis / signal synthesis for various classes, and using transformations based on any orthonormal basis with weight. This proposed approach is based on the concept of Euclidean signal norm square fraction in a given subband of the transformant definition domain. It is shown that the basis for mathematical apparatus of subband analysis is a new class of matrices, called subband ones. Some eigenvalue properties of these matrices are established, and the problem of optimal selection for additive signal components is formulated and solved

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Section: Discussionmentioning

confidence: 99%

“…Note that the equality to the unit of the second integral is obtained on t he basis of the Parseval equality (17) and the orthonormal nature of the eigenvectors. Bearing in mind the decomposition (22) and definition (29), from (20) it is not difficult to get an idea for the characteristic (18)…”

Section:  mentioning

confidence: 99%

Generalized sub band analysis and signal synthesis

Zhilyakov¹,

Белов²,

Oleinik³

et al. 2020

Bulletin EEI

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show abstract

“…The two input multiplexer controlled by a signal called VALID [25]. When VALID is zero, the multiplexer propagates 20kHz high frequency clock pulse to the output CLK; When VALID is one, only 2.5 kHz low frequency clock pulse will be propagated.…”

Section: -Input Multiplexermentioning

confidence: 99%

On-chip ultra low power optical wake-up receiver for wireless sensor nodes targeting structural health monitoring

et al. 2020

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Wireless sensor network (WSN) consists of distributed nodes deployed for monitoring the physical conditions and organizing collected data at the central control unit. Power consumption is the challenges in WSN as the network consists of wireless sensor nodes becomes denser. By utilizing WSN and visible light technology, a simple health monitoring system design can be approached that are smaller in size, faster and lower power consumption. This work focuses on design a low power optical wake-up receiver to reduce the energy consumption of each node in WSN. A wake-up receiver is designed to be always-on for detecting incoming signal and switches on the stand by protocol controller and WSN network for data transmission process. The characteristic of optical transmission and functional circuit of a wake-up receiver has been investigated. A low power optical wake-up receiver has been designed in 180nm Silterra CMOS process technology. The proposed wake-up receiver consumes only 443pW in standby mode and 1.89nW in active mode. The proposed optical wake-up receiver drastically reduces the power consumption by more than one third compared to other wake-up receivers which could be a milestone in the medical field if successfully conducted.

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“…In the following, matrices with elements of the form (21) are called subband ones. In addition to relations (22), (23) and (25), some more specific relations for their own numbers and vectors can also be…”

Section:  mentioning

confidence: 99%

Section:  mentioning

confidence: 99%

Generalized Subband Analysis and Signal Synthesis

2019

Infokommun. tehnol.

View full text Add to dashboard Cite

Currently, one of the main approaches used in analyzing properties and synthesis of signals in various classes is the subband methodology, which is carried out from the position of Fourier transform of signal samples (frequency representations) into subbands of the transform definition domain (transformants). In this case, the main tool, which is widely used for subband analysis (including wavelet analysis), is usage of bandpass filters (mainly those with finite impulse response or FIR filters). The present paper introduces the basics of building a theory forsubband analysis/signal synthesis for various classes, and using transformations based on any orthonormal basis with weight. This proposed approach is based on the concept of Euclidean signal norm square fraction in a given subband of the transformant definition domain. It is shown that the basis for mathematical apparatus of subband analysis is a new class of matrices, called subband ones. Some eigenvalue properties of these matrices are established, and the problem of optimal selection for additive signal components is formulated and solved.

show abstract

A 30mV input battery-less power management system

Cited by 4 publications

References 20 publications

Generalized sub band analysis and signal synthesis

Generalized sub band analysis and signal synthesis

On-chip ultra low power optical wake-up receiver for wireless sensor nodes targeting structural health monitoring

Generalized Subband Analysis and Signal Synthesis

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