In order to achieve higher spectrum efficiency in cognitive radio （CR） systems, a closed-form expression of the optimal decision threshold for soft decision cooperative spectrum sensing based on the minimum total er...In order to achieve higher spectrum efficiency in cognitive radio （CR） systems, a closed-form expression of the optimal decision threshold for soft decision cooperative spectrum sensing based on the minimum total error probability criterion is derived. With the analytical expression of the optimal decision threshold, the impact of different sensing parameters on the threshold value is studied. Theoretical analyses show that the optimal threshold achieves an efficient trade-off between the missed detection probability and the false alarm probability. Simulation results illustrate that the average signal-to-noise ratio （SNR） and the soft combination schemes have a great influence on the optimal threshold value, whereas the number of samples has a weak impact on the optimal threshold value. Furthermore, for the maximal ratio combing （MRC） and the modified deflection coefficient （MDC） schemes, the optimal decision threshold value increases and approaches a corresponding individual limit value while the number of CR users increases. But the number of CR users has a weak influence on the optimal decision threshold for the equal gain combining （EGC） scheme.展开更多
Integration interval and decision threshold issues were investigated for improved transmitted reference pulse cluster （iTRPC-） ultra-wideband （UWB） systems. Our analysis shows that the bit error rate （BER） perfo...Integration interval and decision threshold issues were investigated for improved transmitted reference pulse cluster （iTRPC-） ultra-wideband （UWB） systems. Our analysis shows that the bit error rate （BER） performance of iTRPC-UWB systems can be significantly improved via integration interval determination （IID） and decision threshold optimization. For this purpose, two modifications can be made at the autocorrelation receiver as follows. Firstly, the liD processing is performed for autocorrelation operation to capture multi-path energy as much as possible. Secondly, adaptive decision threshold （ADT） instead of zero decision threshold （ZDT）, is used as estimated optimal decision threshold for symbol detection. Performance of iTRPCUWB systems using liD and ADT was evaluated in realistic IEEE 802.15.4a UWB channel models and the simulation results demonstrated our theoretical analysis.展开更多
Foreground detection is a fundamental step in visual surveillance.However,accurate foreground detection is still a challenging task especially in dynamic backgrounds.In this paper,we present a nonparametric approach t...Foreground detection is a fundamental step in visual surveillance.However,accurate foreground detection is still a challenging task especially in dynamic backgrounds.In this paper,we present a nonparametric approach to foreground detection in dynamic backgrounds.It uses a history of recently pixel values to estimate background model.Besides,the adaptive threshold and spatial coherence are introduced to enhance robustness against false detections.Experimental results indicate that our approach achieves better performance in dynamic backgrounds compared with several approaches.展开更多
Intrusion detection is critical to guaranteeing the safety of the data in the network.Even though,since Internet commerce has grown at a breakneck pace,network traffic kinds are rising daily,and network behavior chara...Intrusion detection is critical to guaranteeing the safety of the data in the network.Even though,since Internet commerce has grown at a breakneck pace,network traffic kinds are rising daily,and network behavior characteristics are becoming increasingly complicated,posing significant hurdles to intrusion detection.The challenges in terms of false positives,false negatives,low detection accuracy,high running time,adversarial attacks,uncertain attacks,etc.lead to insecure Intrusion Detection System(IDS).To offset the existing challenge,the work has developed a secure Data Mining Intrusion detection system(DataMIDS)framework using Functional Perturbation(FP)feature selection and Bengio Nesterov Momentum-based Tuned Generative Adversarial Network(BNM-tGAN)attack detection technique.The data mining-based framework provides shallow learning of features and emphasizes feature engineering as well as selection.Initially,the IDS data are analyzed for missing values based on the Marginal Likelihood Fisher Information Matrix technique(MLFIMT)that identifies the relationship among the missing values and attack classes.Based on the analysis,the missing values are classified as Missing Completely at Random(MCAR),Missing at random(MAR),Missing Not at Random(MNAR),and handled according to the types.Thereafter,categorical features are handled followed by feature scaling using Absolute Median Division based Robust Scalar(AMDRS)and the Handling of the imbalanced dataset.The selection of relevant features is initiated using FP that uses‘3’Feature Selection(FS)techniques i.e.,Inverse Chi Square based Flamingo Search(ICS-FSO)wrapper method,Hyperparameter Tuned Threshold based Decision Tree(HpTT-DT)embedded method,and Xavier Normal Distribution based Relief(XavND-Relief)filter method.Finally,the selected features are trained and tested for detecting attacks using BNM-tGAN.The Experimental analysis demonstrates that the introduced DataMIDS framework produces an accurate diagnosis about the attack with low computation time.The work avoids false alarm rate of attacks and remains to be relatively robust against malicious attacks as compared to existing methods.展开更多
This paper briefly introduces one of the three physical layer implementations of IEEE 802.16a~[1],WirelessMAN-OFDM PHY.Based on the implementation,the combination of Orthogonal Frequency Division Multiplexing(OFDM)and...This paper briefly introduces one of the three physical layer implementations of IEEE 802.16a~[1],WirelessMAN-OFDM PHY.Based on the implementation,the combination of Orthogonal Frequency Division Multiplexing(OFDM)and Space-Time Coding(STC)which is briefly called ST-OFDM in IEEE 802.16a,is investigated under thechannel provided in Ref.[2].Especially,this paper is focused on the influence of the optimal decision threshold on the sys-tern Bit-Error-Rate(BER)performance based on unequal probabilities of sources.The simulations show that when Signal-Noise-Ratio(SNR)is low the optimal decision threshold is obviously superior to the usual one;when SNR is high to someextent,such as 10 dB for 4QAM and 16 dB for 16QAM,we can use the usual decision threshold instead of the optimal展开更多
基金The National Natural Science Foundation of China(No.61271207,61372104)the National Science and Technology Major Project(No.2010ZX0300600201)the Specialized Development Foundation for the Achievement Transformation of Jiangsu Province(No.BA2010023)
文摘In order to achieve higher spectrum efficiency in cognitive radio （CR） systems, a closed-form expression of the optimal decision threshold for soft decision cooperative spectrum sensing based on the minimum total error probability criterion is derived. With the analytical expression of the optimal decision threshold, the impact of different sensing parameters on the threshold value is studied. Theoretical analyses show that the optimal threshold achieves an efficient trade-off between the missed detection probability and the false alarm probability. Simulation results illustrate that the average signal-to-noise ratio （SNR） and the soft combination schemes have a great influence on the optimal threshold value, whereas the number of samples has a weak impact on the optimal threshold value. Furthermore, for the maximal ratio combing （MRC） and the modified deflection coefficient （MDC） schemes, the optimal decision threshold value increases and approaches a corresponding individual limit value while the number of CR users increases. But the number of CR users has a weak influence on the optimal decision threshold for the equal gain combining （EGC） scheme.
基金supported in part by the National Natural Science Foundation of China under Grant 61271262,61473047 and 61572083in part by Shaanxi Provincial Natural Science Foundation under Grant 2015JM6310in part by the Special Fund for Basic Scientific Research of Central Colleges,Chang’an University 310824152010 and 0009-2014G1241043
文摘Integration interval and decision threshold issues were investigated for improved transmitted reference pulse cluster （iTRPC-） ultra-wideband （UWB） systems. Our analysis shows that the bit error rate （BER） performance of iTRPC-UWB systems can be significantly improved via integration interval determination （IID） and decision threshold optimization. For this purpose, two modifications can be made at the autocorrelation receiver as follows. Firstly, the liD processing is performed for autocorrelation operation to capture multi-path energy as much as possible. Secondly, adaptive decision threshold （ADT） instead of zero decision threshold （ZDT）, is used as estimated optimal decision threshold for symbol detection. Performance of iTRPCUWB systems using liD and ADT was evaluated in realistic IEEE 802.15.4a UWB channel models and the simulation results demonstrated our theoretical analysis.
基金supported by Fund of National Science & Technology monumental projects under Grants No.61105015,NO.61401239,NO.2012-364-641-209
文摘Foreground detection is a fundamental step in visual surveillance.However,accurate foreground detection is still a challenging task especially in dynamic backgrounds.In this paper,we present a nonparametric approach to foreground detection in dynamic backgrounds.It uses a history of recently pixel values to estimate background model.Besides,the adaptive threshold and spatial coherence are introduced to enhance robustness against false detections.Experimental results indicate that our approach achieves better performance in dynamic backgrounds compared with several approaches.
文摘Intrusion detection is critical to guaranteeing the safety of the data in the network.Even though,since Internet commerce has grown at a breakneck pace,network traffic kinds are rising daily,and network behavior characteristics are becoming increasingly complicated,posing significant hurdles to intrusion detection.The challenges in terms of false positives,false negatives,low detection accuracy,high running time,adversarial attacks,uncertain attacks,etc.lead to insecure Intrusion Detection System(IDS).To offset the existing challenge,the work has developed a secure Data Mining Intrusion detection system(DataMIDS)framework using Functional Perturbation(FP)feature selection and Bengio Nesterov Momentum-based Tuned Generative Adversarial Network(BNM-tGAN)attack detection technique.The data mining-based framework provides shallow learning of features and emphasizes feature engineering as well as selection.Initially,the IDS data are analyzed for missing values based on the Marginal Likelihood Fisher Information Matrix technique(MLFIMT)that identifies the relationship among the missing values and attack classes.Based on the analysis,the missing values are classified as Missing Completely at Random(MCAR),Missing at random(MAR),Missing Not at Random(MNAR),and handled according to the types.Thereafter,categorical features are handled followed by feature scaling using Absolute Median Division based Robust Scalar(AMDRS)and the Handling of the imbalanced dataset.The selection of relevant features is initiated using FP that uses‘3’Feature Selection(FS)techniques i.e.,Inverse Chi Square based Flamingo Search(ICS-FSO)wrapper method,Hyperparameter Tuned Threshold based Decision Tree(HpTT-DT)embedded method,and Xavier Normal Distribution based Relief(XavND-Relief)filter method.Finally,the selected features are trained and tested for detecting attacks using BNM-tGAN.The Experimental analysis demonstrates that the introduced DataMIDS framework produces an accurate diagnosis about the attack with low computation time.The work avoids false alarm rate of attacks and remains to be relatively robust against malicious attacks as compared to existing methods.
文摘This paper briefly introduces one of the three physical layer implementations of IEEE 802.16a~[1],WirelessMAN-OFDM PHY.Based on the implementation,the combination of Orthogonal Frequency Division Multiplexing(OFDM)and Space-Time Coding(STC)which is briefly called ST-OFDM in IEEE 802.16a,is investigated under thechannel provided in Ref.[2].Especially,this paper is focused on the influence of the optimal decision threshold on the sys-tern Bit-Error-Rate(BER)performance based on unequal probabilities of sources.The simulations show that when Signal-Noise-Ratio(SNR)is low the optimal decision threshold is obviously superior to the usual one;when SNR is high to someextent,such as 10 dB for 4QAM and 16 dB for 16QAM,we can use the usual decision threshold instead of the optimal
