scholarly journals 137 Gb/s PAM-4 Transmissions at 850 nm over 40 cm Optical Backplane with 25 G Devices with Improved Neural Network-Based Equalization

2019 ◽  
Vol 9 (23) ◽  
pp. 5095
Author(s):  
Qianwu Zhang ◽  
Yuntong Jiang ◽  
Hai Zhou ◽  
Chuanlu Deng ◽  
Shuaihang Duan ◽  
...  
Keyword(s):  
Neural Network ◽  
Forward Error Correction ◽  
Optical Power ◽  
Pulse Amplitude ◽  
Performance Comparison ◽  
Decision Feedback ◽  
Bit Rate ◽  
Optical Backplane ◽  
The Impact ◽  
Equalization Method

An improved neural network-based equalization method is proposed and experimentally demonstrated. The up-to-137 Gb/s transmission of four level pulse amplitude modulation (PAM-4) signals with 25 G class 850 nm optical devices is achieved over an in-house fabricated 40 cm optical backplane. An in-depth investigation is conducted regarding the impact of delayed taps and spans on equalization performance. A performance comparison of the proposed method with the traditional maximum likelihood sequence estimation (MLSE) and decision feedback equalization (DFE) is also undertaken. For the bit rate from 80 to 100 Gb/s, the proposed method achieves an adopted hard-decision forward error correction (HD-FEC) requirement at a received optical power (RoP) of −9 and −8 dBm, while DFE and MLSE cannot meet the HD-FEC requirement. When the bit rate increases from 120 to 137 Gb/s, the proposed equalization method still successfully maintains the acceptable system performance at an RoP of −4 and −2.5 dBm. Furthermore, the specific bit error rate (BER) performances for varied maximum achievable bit rate under different RoPs by applying MLSE and the proposed method are also analyzed. This provides an important potential solution to realize the future data centers.

scholarly journals 100 Gbaud On–Off Keying/Pulse Amplitude Modulation Links in C-Band for Short-Reach Optical Interconnects

2021 ◽  
Vol 11 (9) ◽  
pp. 4284
Author(s):  
Oskars Ozolins ◽  
Xiaodan Pang ◽  
Aleksejs Udalcovs ◽  
Richard Schatz ◽  
Sandis Spolitis ◽  
...  
Keyword(s):  
Amplitude Modulation ◽  
Optical Interconnects ◽  
High Speed ◽  
Extinction Ratio ◽  
Optical Power ◽  
Single Mode ◽  
Pulse Amplitude ◽  
Single Mode Fiber ◽  
Decision Feedback ◽  
Pulse Amplitude Modulation

We experimentally evaluate the high-speed on–off keying (OOK) and four-level pulse amplitude modulation (PAM4) transmitter’s performance in C-band for short-reach optical interconnects. We demonstrate up to 100 Gbaud OOK and PAM4 transmission over a 400 m standard single-mode fiber with a monolithically integrated externally modulated laser (EML) having 100 GHz 3 dB bandwidth with 2 dB ripple. We evaluate its capabilities to enable 800 GbE client-side links based on eight, and even four, optical lanes for optical interconnect applications. We study the equalizer’s complexity when increasing the baud rate of PAM4 signals. Furthermore, we extend our work with numerical simulations showing the required received optical power (ROP) for a certain bit error rate (BER) for the different combinations of the effective number of bits (ENOB) and extinction ratio (ER) at the transmitter. We also show a possibility to achieve around 1 km dispersion uncompensated transmission with a simple decision feedback equalizer (DFE) for a 100 Gbaud OOK, PAM4, and eight-level PAM (PAM8) link having the received power penalty of around 1 dB.

scholarly journals Imbalanced Mach-Zehnder Modulator for Fading Suppression in Dispersion-Uncompensated Direct Detection System

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2866
Author(s):  
Yixiao Zhu ◽  
Xin Miao ◽  
Qi Wu ◽  
Longjie Yin ◽  
Weisheng Hu
Keyword(s):  
Forward Error Correction ◽  
Direct Detection ◽  
Detection System ◽  
Single Mode ◽  
Pulse Amplitude ◽  
Single Mode Fiber ◽  
Error Rates ◽  
Transmission Experiment ◽  
Mach Zehnder Modulator ◽  
The Impact

In this work, we systematically analyze the impact of three kinds of Mach-Zehnder modulator (MZM) imbalances, including bias deviation, amplitude mismatch, and differential time skew in intensity-modulation direct-detection (IM-DD) links. It is shown that, for power fading limited transmission, the imbalances can be utilized as advantages rather than impairments. Specifically, the bias deviation with single-arm driven mode and amplitude mismatch with differential driven mode can increase the available bandwidth by shifting the frequency of fading notches. Meanwhile, time skew provides another way to avoid fading by shaping the double sideband (DSB) signal into a vestigial sideband (VSB) with an asymmetrical transfer function. In the transmission experiment, 34 Gbaud Nyquist 6/8-ary pulse amplitude modulation (PAM-6/8) signals are used for investigation in a 20 km dispersion-uncompensated standard single-mode fiber (SSMF) link. With the help of a Volterra nonlinear equalizer, all three kinds of imbalances can achieve bit-error rates (BERs) below the 7% and 20% hard-decision forward error correction (HD-FEC) thresholds for PAM-6 and PAM-8 signals, respectively. The received power sensitivity is also compared at the back-to-back (BTB) case and after fiber transmission. Both numerical simulation and experimental demonstration confirm that the dispersion-induced power fading can be effectively suppressed with bias, amplitude, or skew imbalance, providing a feasible solution for transmission distance extension of C-band DD links.

scholarly journals Optical Power Budget of 25+ Gbps IM/DD PON with Digital Signal Post-Equalization

2020 ◽  
Vol 10 (17) ◽  
pp. 6106
Author(s):  
Aleksejs Udalcovs ◽  
Toms Salgals ◽  
Lu Zhang ◽  
Xiaodan Pang ◽  
Anders Djupsjöbacka ◽  
...  
Keyword(s):  
Optical Networks ◽  
Direct Detection ◽  
Optical Power ◽  
Digital Signal ◽  
Single Mode ◽  
Pulse Amplitude ◽  
Power Splitting ◽  
Power Budget ◽  
Sustainable Solutions ◽  
The Impact

While infrastructure providers are expanding their portfolio to offer sustainable solutions for beyond 10 Gbps in the access segment of optical networks, we experimentally compare several modulation format alternatives for future passive optical networks (PONs) aiming to deliver 25+ Gbps net-rates. As promising candidates, we consider the intensity modulation direct detection (IM/DD) schemes such as electrical duobinary (EDB) and 4-level and 8-level pulse amplitude modulations (PAM-4/8). They are more spectrally efficient than the conventional non-return-to-zero on-off-keying (NRZ-OOK) used in current 10G PONs. As we move to higher rates, digital equalization enhances the performance by smoothening the systems imperfection. However, the impact that such equalization has on the optical power budget remains unclear. Therefore, in this article, we fairly compare the optical power budget values of a time division multiplexed PON (TDM-PON) exploiting a linear digital signal equalization at the receiver side. We consider the conventional PON configuration (20 km of single-mode fiber (SMF), 1:N optical power splitting) with IM/DD and net-rates above 25 Gbps. Furthermore, we focus on a downstream transmission imposing the bandwidth limitations of 10G components using a digital filter before the detection. The obtained results show that the use of a digital post-equalization with 43 feed-forward (FF) and 21 feedback (FB) taps can significantly improve the signal quality enabling new alternatives and enhancing the optical power budget.

scholarly journals Quantization of Weights of Neural Networks with Negligible Decreasing of Prediction Accuracy

2021 ◽  
Vol 50 (3) ◽  
pp. 558-569
Author(s):  
Zoran Peric ◽  
Bojan Denic ◽  
Milan Savic ◽  
Milan Dincic ◽  
Darko Mihajlov
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Prediction Accuracy ◽  
Network Performance ◽  
Dynamic Range ◽  
Mean Squared Error ◽  
Real Data ◽  
Quantization Noise ◽  
Bit Rate ◽  
The Impact

Quantization and compression of neural network parameters using the uniform scalar quantization is carried out in this paper. The attractiveness of the uniform scalar quantizer is reflected in a low complexity and relatively good performance, making it the most popular quantization model. We present a design approach for the memoryless Laplacian source with zero-mean and unit variance, which is based on iterative rule and uses the minimal mean-squared error distortion as a performance criterion. In addition, we derive closed-form expressions for SQNR (Signal to Quantization Noise Ratio) in a wide dynamic range of variance of input data. To show effectiveness on real data, the proposed quantizer is used to compress the weights of neural networks using bit rates from 9 to 16 bps (bits/sample) instead of standardly used 32 bps full precision bit rate. The impact of weights compression on the NN (neural network) performance is analyzed, indicating good matching with the theoretical results and showing negligible decreasing of the prediction accuracy of the NN even in the case of high variance-mismatch between the variance of NN weights and the variance used for the design of quantizer, if the value of the bit-rate is properly chosen according to the rule proposed in the paper.

scholarly journals The Utilization of Artificial Neural Network Equalizer in Optical Camera Communications

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2826
Author(s):  
Othman Isam Younus ◽  
Navid Bani Hassan ◽  
Zabih Ghassemlooy ◽  
Stanislav Zvanovec ◽  
Luis Nero Alves ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Bit Error Rate ◽  
Error Rate ◽  
Forward Error Correction ◽  
Light Emitting Diode ◽  
Pulse Amplitude ◽  
Eye Diagram ◽  
Artificial Neural

In this paper, we propose and validate an artificial neural network-based equalizer for the constant power 4-level pulse amplitude modulation in an optical camera communications system. We introduce new terminology to measure the quality of the communications link in terms of the number of row pixels per symbol Npps, which allows a fair comparison considering the progress made in the development of the current image sensors in terms of the frame rates and the resolutions of each frame. Using the proposed equalizer, we experimentally demonstrate a non-flickering system using a single light-emitting diode (LED) with Npps of 20 and 30 pixels/symbol for the unequalized and equalized systems, respectively. Potential transmission rates of up to 18.6 and 24.4 kbps are achieved with and without the equalization, respectively. The quality of the received signal is assessed using the eye-diagram opening and its linearity and the bit error rate performance. An acceptable bit error rate (below the forward error correction limit) and an improvement of ~66% in the eye linearity are achieved using a single LED and a typical commercial camera with equalization.

Research on behavior recognition based on feature fusion of automatic coder and recurrent neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8927-8935
Author(s):  
Bing Zheng ◽  
Dawei Yun ◽  
Yan Liang
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Behavior Pattern ◽  
Rapid Development ◽  
Video Data ◽  
Support Vector ◽  
Behavior Recognition ◽  
Learning Methods ◽  
The Impact ◽  
Internet Of Things Technology

Under the impact of COVID-19, research on behavior recognition are highly needed. In this paper, we combine the algorithm of self-adaptive coder and recurrent neural network to realize the research of behavior pattern recognition. At present, most of the research of human behavior recognition is focused on the video data, which is based on the video number. At the same time, due to the complexity of video image data, it is easy to violate personal privacy. With the rapid development of Internet of things technology, it has attracted the attention of a large number of experts and scholars. Researchers have tried to use many machine learning methods, such as random forest, support vector machine and other shallow learning methods, which perform well in the laboratory environment, but there is still a long way to go from practical application. In this paper, a recursive neural network algorithm based on long and short term memory (LSTM) is proposed to realize the recognition of behavior patterns, so as to improve the accuracy of human activity behavior recognition.

European Economies Stability Faced With Potential Outburst of Sovereign Debt Crisis. An Empirical Study Using Neural Network

2013 ◽  
Vol 12 (2) ◽  
pp. 3255-3260
Author(s):  
Stelian Stancu ◽  
Alexandra Maria Constantin
Keyword(s):  
Neural Network ◽  
Sovereign Debt ◽  
Debt Crisis ◽  
Banking System ◽  
Sovereign Debt Crisis ◽  
European Level ◽  
Continuous Growth ◽  
Economic Context ◽  
European Economies ◽  
The Impact

Instilment, on a European level, of a state incompatible with the state of stability on a macroeconomic level and in the financial-banking system lead to continuous growth of vulnerability of European economies, situated at the verge of an outburst of sovereign debt crises. In this context, the current papers main objective is to produce a study regarding the vulnerability of European economies faced with potential outburst of sovereign debt crisis, which implies quantitative analysis of the impact of sovereign debt on the sensitivity of the European Unions economies. The paper also entails the following specific objectives: completing an introduction in the current European economic context, conceptualization of the notion of “sovereign debt crisis, presenting the methodology and obtained empirical results, as well as exposition of the conclusions.

Application of vacuum belt press filters for cane mud filtration and performance comparison with rotary filters

2014 ◽  
pp. 298-301 ◽  
Author(s):  
Arnaud Petit
Keyword(s):  
Electricity Consumption ◽  
Performance Comparison ◽  
Operating Conditions ◽  
Vacuum Filter ◽  
Sugar Mill ◽  
Belt Press ◽  
Vacuum Belt ◽  
And Performance ◽  
Mud Filtration ◽  
The Impact

Bois-Rouge factory, an 8000 t/d cane Reunionese sugarcane mill, has fully equipped its filtration station with vacuum belt press filters since 2010, the first one being installed in 2009. The present study deals with this 3-year experience and discusses operating conditions, electricity consumption, performance and optimisation. The comparison with the more classical rotary drum vacuum filter station of Le Gol sugar mill highlights advantages of vacuum belt press filters: high filtration efficiency, low filter cake mass and sucrose content, low total solids content in filtrate and low power consumption. However, this technology needs a mud conditioning step and requires a large amount of water to improve mud quality, mixing of flocculant and washing of filter belts. The impact on the energy balance of the sugar mill is significant. At Bois-Rouge mill, studies are underway to reduce the water consumption by recycling low d.s. filtrate and by dry cleaning the filter belts.

scholarly journals Artificial neural network, predictor variables and sensitivity threshold for DNA methylation-based age prediction using blood samples

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhonghui Thong ◽  
Jolena Ying Ying Tan ◽  
Eileen Shuzhen Loo ◽  
Yu Wei Phua ◽  
Xavier Liang Shun Chan ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Regression Model ◽  
Sensitivity Threshold ◽  
Ann Model ◽  
Blood Samples ◽  
Ann Models ◽  
Artificial Neural ◽  
The Impact ◽  
Age Prediction

AbstractRegression models are often used to predict age of an individual based on methylation patterns. Artificial neural network (ANN) however was recently shown to be more accurate for age prediction. Additionally, the impact of ethnicity and sex on our previous regression model have not been studied. Furthermore, there is currently no age prediction study investigating the lower limit of input DNA at the bisulfite treatment stage prior to pyrosequencing. Herein, we evaluated both regression and ANN models, and the impact of ethnicity and sex on age prediction for 333 local blood samples using three loci on the pyrosequencing platform. Subsequently, we trained a one locus-based ANN model to reduce the amount of DNA used. We demonstrated that the ANN model has a higher accuracy of age prediction than the regression model. Additionally, we showed that ethnicity did not affect age prediction among local Chinese, Malays and Indians. Although the predicted age of males were marginally overestimated, sex did not impact the accuracy of age prediction. Lastly, we present a one locus, dual CpG model using 25 ng of input DNA that is sufficient for forensic age prediction. In conclusion, the two ANN models validated would be useful for age prediction to provide forensic intelligence leads.

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