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您的检索式：作者名="Sibghat Ullah"
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| 1 | Colorless WDM-PON Using Single Side Band Carrier Suppressed Signals Mitigating Carrier Rayleigh Backscattering显示文摘A new scheme is offered for minimizing carrier Rayleigh backscattering(CRB) in single feeder fiber based wavelength division multiplexed passive optical network(WDM-PON). The proposed scheme is based on single side band carrier suppressed(SSBCS) signal, both at network and receiver sides, used for the first time at optical line terminal(OLT) and optical network unit(ONU) sides. We use dual-drive Mach-zehnder modulator(DD-MZM) for generating SSB-CS signals, which decreases the expense per bit in full transmission. SSB-CS mitigates CRB, both at OLT and ONU sides, because of having no chance of reflections from the carrier. Since no extra dedicated RF or laser source is used at ONU side, we thus achieve cost effective colorless WDM-PON system. Suppressed signals from four channels, each of 10 Gbps, are multiplexed before injecting into the fiber span of 25 km at OLT. At ONU side, half of the downlink power is used for re-modulating the data signal. The simulation results show an errorfree transmission. Moreover, the detailed power budget calculations show that the proposed scheme can be sought out for splitting ratio up to 128. Hence it offers enough system's margin for unseen losses. | Rahat Ullah Bo Liu Qi Zhang Yousaf Khan Amjad Ali Qinghua Tian Feng Tian M.Saad Khan Tabinda Salam Sibghat Ullah Lijia Zhang Xiangjun Xin | 2016 | China Communications2016，13，12： | 0 |
| 2 | Deep Learning-Based Trees Disease Recognition and Classification Using Hyperspectral Data显示文摘Crop diseases have a significant impact on plant growth and can lead to reduced yields.Traditional methods of disease detection rely on the expertise of plant protection experts,which can be subjective and dependent on individual experience and knowledge.To address this,the use of digital image recognition technology and deep learning algorithms has emerged as a promising approach for automating plant disease identification.In this paper,we propose a novel approach that utilizes a convolutional neural network(CNN)model in conjunction with Inception v3 to identify plant leaf diseases.The research focuses on developing a mobile application that leverages this mechanism to identify diseases in plants and provide recommendations for overcoming specific diseases.The models were trained using a dataset consisting of 80,848 images representing 21 different plant leaves categorized into 60 distinct classes.Through rigorous training and evaluation,the proposed system achieved an impressive accuracy rate of 99%.This mobile application serves as a convenient and valuable advisory tool,providing early detection and guidance in real agricultural environments.The significance of this research lies in its potential to revolutionize plant disease detection and management practices.By automating the identification process through deep learning algorithms,the proposed system eliminates the subjective nature of expert-based diagnosis and reduces dependence on individual expertise.The integration of mobile technology further enhances accessibility and enables farmers and agricultural practitioners to swiftly and accurately identify diseases in their crops. | Uzair Aslam Bhatti Sibghat Ullah Bazai Shumaila Hussain Shariqa Fakhar Chin Soon Ku Shah Marjan Por Lip Yee Liu Jing | 2023 | Computers, Materials & Continua2023，77，10： | 0 |
| 3 | Polarization-based optimal detection scheme for digital self-interference cancellation in full-duplex system显示文摘In order to detect and cancel the self-interference(SI)signal from desired binary phase-shift keying(BPSK)signal,the polarization-based optimal detection(POD)scheme for cancellation of digital SI in a full-duplex(FD)system is proposed.The POD scheme exploits the polarization domain to isolate the desired signal from the SI signal and then cancel the SI to obtain the interference-free desired signal at the receiver.In FD communication,after antenna and analog cancellation,the receiver still contains residual SI due to non-linearities of hardware imperfections.In POD scheme,a likelihood ratio expression is obtained,which isolates and detects SI bits from the desired bits.After isolation of these signal points,the POD scheme cancels the residual SI.As compared to the conventional schemes,the proposed POD scheme gives significantly low bit error rate(BER),a clear constellation diagram to obtain the boundary between desired and SI signal points,and increases the receiver's SI cancellation performance in low signal to interference ratio(SIR)environment. | Adil Khan Zhang Jinling Muhammad Ayzed Mirza Sibghat Ullah Erum Ab basi Babar Hayat | 2020 | The Journal of China Universities of Posts and Telecommunications2020，27，3： | 0 |
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