Performance evaluation of Sigma Delta Zero Crossing DPLL

Author(s):  
Qassim Nasir ◽  
Saleh R. Al-Araji
2020 ◽  
Vol 10 (17) ◽  
pp. 5785
Author(s):  
Huishan Zhai ◽  
Bingo Wing-Kuen Ling

This paper is an extension of the existing works on the frequency-domain-based bit flipping control strategy for stabilizing the single-bit high-order interpolative sigma delta modulator. In particular, this paper proposes the implementation and performs the performance evaluation of the control strategy. For the implementation, a frequency detector is used to detect the resonance frequencies of the input sequence of the sigma delta modulator. Then, a neural-network-based controller is used for finding the solution of the integer programming problem. Finally, the buffers and the combinational logic gates as well as an inverter are used for implementing the proposed control strategy. For the performance evaluation, the stability region in terms of the input dynamical range is evaluated. It is found that the control strategy can significantly increase the input dynamical range from 0.24 to 0.58. Besides, the control strategy can be applied to a wider class of the input signals compared to the clipping method.


2020 ◽  
Vol 67 (12) ◽  
pp. 2813-2817
Author(s):  
Johannes Wagner ◽  
Patrick Vogelmann ◽  
Maurits Ortmanns

1989 ◽  
Vol 24 (2) ◽  
pp. 256-266 ◽  
Author(s):  
S.R. Norsworthy ◽  
I.G. Post ◽  
H.S. Fetterman

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Aurel A. Lazar ◽  
Yevgeniy B. Slutskiy

We present a formal methodology for identifying a channel in a system consisting of a communication channel in cascade with an asynchronous sampler. The channel is modeled as a multidimensional filter, while models of asynchronous samplers are taken from neuroscience and communications and include integrate-and-fire neurons, asynchronous sigma/delta modulators and general oscillators in cascade with zero-crossing detectors. We devise channel identification algorithms that recover a projection of the filter(s) onto a space of input signals loss-free for both scalar and vector-valued test signals. The test signals are modeled as elements of a reproducing kernel Hilbert space (RKHS) with a Dirichlet kernel. Under appropriate limiting conditions on the bandwidth and the order of the test signal space, the filter projection converges to the impulse response of the filter. We show that our results hold for a wide class of RKHSs, including the space of finite-energy bandlimited signals. We also extend our channel identification results to noisy circuits.


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