Implementation of a real-time, frequency selective, RF channel simulator using a hybrid DSP-FPGA architecture

2002 ◽  
Author(s):  
J.R. Papenfuss ◽  
M.A. Wickert
Keyword(s):  
Real Time ◽  
Time Frequency ◽  
Fpga Architecture ◽  
Frequency Selective ◽  
Channel Simulator

Acoustic-based Upper Facial Action Recognition for Smart Eyewear

2021 ◽  
Vol 5 (2) ◽  
pp. 1-28
Author(s):  
Wentao Xie ◽  
Qian Zhang ◽  
Jin Zhang
Keyword(s):  
Frequency Domain ◽  
Orthogonal Frequency Division Multiplexing ◽  
Interaction Mechanism ◽  
Phase Changes ◽  
Experimental Result ◽  
Selective Fading ◽  
Time Frequency ◽  
Facial Action ◽  
Frequency Selective Fading ◽  
Frequency Selective

Smart eyewear (e.g., AR glasses) is considered to be the next big breakthrough for wearable devices. The interaction of state-of-the-art smart eyewear mostly relies on the touchpad which is obtrusive and not user-friendly. In this work, we propose a novel acoustic-based upper facial action (UFA) recognition system that serves as a hands-free interaction mechanism for smart eyewear. The proposed system is a glass-mounted acoustic sensing system with several pairs of commercial speakers and microphones to sense UFAs. There are two main challenges in designing the system. The first challenge is that the system is in a severe multipath environment and the received signal could have large attenuation due to the frequency-selective fading which will degrade the system's performance. To overcome this challenge, we design an Orthogonal Frequency Division Multiplexing (OFDM)-based channel state information (CSI) estimation scheme that is able to measure the phase changes caused by a facial action while mitigating the frequency-selective fading. The second challenge is that because the skin deformation caused by a facial action is tiny, the received signal has very small variations. Thus, it is hard to derive useful information directly from the received signal. To resolve this challenge, we apply a time-frequency analysis to derive the time-frequency domain signal from the CSI. We show that the derived time-frequency domain signal contains distinct patterns for different UFAs. Furthermore, we design a Convolutional Neural Network (CNN) to extract high-level features from the time-frequency patterns and classify the features into six UFAs, namely, cheek-raiser, brow-raiser, brow-lower, wink, blink and neutral. We evaluate the performance of our system through experiments on data collected from 26 subjects. The experimental result shows that our system can recognize the six UFAs with an average F1-score of 0.92.

A New Method for Phase Difference Estimation Based on Time-Varying Signal Model

2013 ◽  
Vol 333-335 ◽  
pp. 650-655
Author(s):  
Peng Hui Niu ◽  
Yin Lei Qin ◽  
Shun Ping Qu ◽  
Yang Lou
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Phase Difference ◽  
Time Signal ◽  
Time Interval ◽  
Time Varying ◽  
Signal Model ◽  
Time Frequency ◽  
Mass Flowmeter ◽  
Coriolis Mass Flowmeter

A new signal processing method for phase difference estimation was proposed based on time-varying signal model, whose frequency, amplitude and phase are time-varying. And then be applied Coriolis mass flowmeter signal. First, a bandpass filtering FIR filter was applied to filter the sensor output signal in order to improve SNR. Then, the signal frequency could be calculated based on short-time frequency estimation. Finally, by short window intercepting, the DTFT algorithm with negative frequency contribution was introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference obtained, the time interval of two signals was calculated. Simulation results show that the algorithms studied are efficient. Furthermore, the computation of algorithms studied is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.

scholarly journals A real-time time-frequency based instantaneous frequency estimator

2013 ◽  
Vol 93 (5) ◽  
pp. 1392-1397 ◽  
Author(s):  
Ljubiša Stanković ◽  
Miloš Daković ◽  
Thayananthan Thayaparan
Keyword(s):  
Real Time ◽  
Instantaneous Frequency ◽  
Time Frequency ◽  
Frequency Estimator

Implementation of a real-time mobile channel simulator using a DSP chip

1991 ◽  
Vol 40 (4) ◽  
pp. 709-714 ◽  
Author(s):  
R.A. Goubran ◽  
H.M. Hafez ◽  
A.U.H. Sheikh
Keyword(s):  
Real Time ◽  
Mobile Channel ◽  
Channel Simulator

On the Development of a Real Time Wide Band Channel Simulator for Leo Satellite Channels

1997 ◽  
pp. 131-139 ◽  
Author(s):  
M. Tykesson ◽  
L. Sabel ◽  
R. Wozniak ◽  
T. Zierch ◽  
D. Tran ◽  
...  
Keyword(s):  
Real Time ◽  
Wide Band ◽  
Satellite Channels ◽  
Leo Satellite ◽  
Channel Simulator
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