The sine transform can be used as a tool to conquer the problems of discrete multi-tone (DMT) systems to increase the bit rate. In the proposed discrete sine transform based discrete multi-tone (DST-DMT) system, we ma...The sine transform can be used as a tool to conquer the problems of discrete multi-tone (DMT) systems to increase the bit rate. In the proposed discrete sine transform based discrete multi-tone (DST-DMT) system, we make use of the energy compaction property of the DST to reduce the channel effects on the transmitted signals. The mathematical model of the proposed DST system is presented in the paper. Simulation experiments have been carried out to test the effect of the proposed DST-DMT system. The results of these experiments show that the performance of the DST-DMT system is better than that of the traditional FFT-DMT system. The results also show that employing the proposed TEQ in the DST-DMT system can increase the bit rate by about 2.57 Mbps.展开更多
该文介绍了离散时间傅里叶变换(Discrete Time Fourier Transform,DTFT)的一种等价定义式,分析了DTFT与线性调频Z变换(Chirp-Z transform)的联系与区别,推导出DTFT是一种特殊形式的Chirp-Z变换,具有频谱细化特性。设计了DTFT的快速算法...该文介绍了离散时间傅里叶变换(Discrete Time Fourier Transform,DTFT)的一种等价定义式,分析了DTFT与线性调频Z变换(Chirp-Z transform)的联系与区别,推导出DTFT是一种特殊形式的Chirp-Z变换,具有频谱细化特性。设计了DTFT的快速算法,给出了算法实现步骤。算法计算量分析表明:在相同频率分辨率下,DTFT快速算法的计算量比Chirp-Z变换快速算法小。仿真结果验证了理论推导的正确性和DTFT在频率估计方面的优越性。展开更多
Automatic seizure detection is important for fast detection of the seizure because the way that the expert denotes and searches for seizure in the long signal takes time. The most common way to detect seizures automat...Automatic seizure detection is important for fast detection of the seizure because the way that the expert denotes and searches for seizure in the long signal takes time. The most common way to detect seizures automatically is to use an electroencephalogram(EEG). Many studies have used feature extraction that needs time for calculation. In this study, sliding discrete Fourier transform(SDFT) was applied for conversion to a frequency domain without using a window, which was compared with using window for feature selection. SDFT was calculated for each time series sample directly without any delay by using a simple infinite impulse response(IIR)structure. The EEG database of Bonn University was used to test the proposed method, and two cases were defined to examine a two-classifier feedforward neural network and an adaptive network-based fuzzy inference system. Results revealed that the maximum accuracies were 93% without delay and 99.8% with a one-second delay. This delay accrued because the average was taken for the results with a one-second window.展开更多
文摘The sine transform can be used as a tool to conquer the problems of discrete multi-tone (DMT) systems to increase the bit rate. In the proposed discrete sine transform based discrete multi-tone (DST-DMT) system, we make use of the energy compaction property of the DST to reduce the channel effects on the transmitted signals. The mathematical model of the proposed DST system is presented in the paper. Simulation experiments have been carried out to test the effect of the proposed DST-DMT system. The results of these experiments show that the performance of the DST-DMT system is better than that of the traditional FFT-DMT system. The results also show that employing the proposed TEQ in the DST-DMT system can increase the bit rate by about 2.57 Mbps.
文摘该文介绍了离散时间傅里叶变换(Discrete Time Fourier Transform,DTFT)的一种等价定义式,分析了DTFT与线性调频Z变换(Chirp-Z transform)的联系与区别,推导出DTFT是一种特殊形式的Chirp-Z变换,具有频谱细化特性。设计了DTFT的快速算法,给出了算法实现步骤。算法计算量分析表明:在相同频率分辨率下,DTFT快速算法的计算量比Chirp-Z变换快速算法小。仿真结果验证了理论推导的正确性和DTFT在频率估计方面的优越性。
文摘Automatic seizure detection is important for fast detection of the seizure because the way that the expert denotes and searches for seizure in the long signal takes time. The most common way to detect seizures automatically is to use an electroencephalogram(EEG). Many studies have used feature extraction that needs time for calculation. In this study, sliding discrete Fourier transform(SDFT) was applied for conversion to a frequency domain without using a window, which was compared with using window for feature selection. SDFT was calculated for each time series sample directly without any delay by using a simple infinite impulse response(IIR)structure. The EEG database of Bonn University was used to test the proposed method, and two cases were defined to examine a two-classifier feedforward neural network and an adaptive network-based fuzzy inference system. Results revealed that the maximum accuracies were 93% without delay and 99.8% with a one-second delay. This delay accrued because the average was taken for the results with a one-second window.
