A method based on syntactic pattern recognition was presented to automatically classify whistles of bottlenose dolphin. Dolphin whistles have typically been characterized in terms of their instantaneous frequency as a...A method based on syntactic pattern recognition was presented to automatically classify whistles of bottlenose dolphin. Dolphin whistles have typically been characterized in terms of their instantaneous frequency as a function of time, which is also known as ＂whistle contour＂. The frequency variation features of a whistle were extracted according to its contour. Then, the frequency variation features were used for learning grammatical patterns. A whistle was classified according to grammatical pattern of its frequency variation features. The exper- imental results showed that the classification accuracy of the proposed method was 95%. The method can provide technical support for acoustic study of dolphins＇ biological behavior.展开更多
Recently,bionic signals have been used to achieve covert underwater acoustic communication(UWAC)with high signal-to-noise ratios(SNRs)over transmission systems.A high SNR allows the attackers to proceed with their mis...Recently,bionic signals have been used to achieve covert underwater acoustic communication(UWAC)with high signal-to-noise ratios(SNRs)over transmission systems.A high SNR allows the attackers to proceed with their mischievous goals and makes transmission systems vulnerable against malicious attacks.In this paper we propose an improved Merkle hash tree based secure scheme that can resist current underwater attacks,i.e.,replay attack,fabricated message attack,message-altering attack,and analyst attack.Security analysis is performed to prove that the proposed scheme can resist these types of attacks.Performance evaluations show that the proposed scheme can meet UWAC limitations due to its efficiency regarding energy consumption,communication overhead,and computation cost.展开更多
文摘A method based on syntactic pattern recognition was presented to automatically classify whistles of bottlenose dolphin. Dolphin whistles have typically been characterized in terms of their instantaneous frequency as a function of time, which is also known as ＂whistle contour＂. The frequency variation features of a whistle were extracted according to its contour. Then, the frequency variation features were used for learning grammatical patterns. A whistle was classified according to grammatical pattern of its frequency variation features. The exper- imental results showed that the classification accuracy of the proposed method was 95%. The method can provide technical support for acoustic study of dolphins＇ biological behavior.
文摘Recently,bionic signals have been used to achieve covert underwater acoustic communication(UWAC)with high signal-to-noise ratios(SNRs)over transmission systems.A high SNR allows the attackers to proceed with their mischievous goals and makes transmission systems vulnerable against malicious attacks.In this paper we propose an improved Merkle hash tree based secure scheme that can resist current underwater attacks,i.e.,replay attack,fabricated message attack,message-altering attack,and analyst attack.Security analysis is performed to prove that the proposed scheme can resist these types of attacks.Performance evaluations show that the proposed scheme can meet UWAC limitations due to its efficiency regarding energy consumption,communication overhead,and computation cost.
