Spectral subtraction is used in this research as a method to remove noise from noisy speech signals in the frequency domain. This method consists of computing the spectrum of the noisy speech using the Fast Fourier Tr...Spectral subtraction is used in this research as a method to remove noise from noisy speech signals in the frequency domain. This method consists of computing the spectrum of the noisy speech using the Fast Fourier Transform (FFT) and subtracting the average magnitude of the noise spectrum from the noisy speech spectrum. We applied spectral subtraction to the speech signal “Real graph”. A digital audio recorder system embedded in a personal computer was used to sample the speech signal “Real graph” to which we digitally added vacuum cleaner noise. The noise removal algorithm was implemented using Matlab software by storing the noisy speech data into Hanning time-widowed half-overlapped data buffers, computing the corresponding spectrums using the FFT, removing the noise from the noisy speech, and reconstructing the speech back into the time domain using the inverse Fast Fourier Transform (IFFT). The performance of the algorithm was evaluated by calculating the Speech to Noise Ratio (SNR). Frame averaging was introduced as an optional technique that could improve the SNR. Seventeen different configurations with various lengths of the Hanning time windows, various degrees of data buffers overlapping, and various numbers of frames to be averaged were investigated in view of improving the SNR. Results showed that using one-fourth overlapped data buffers with 128 points Hanning windows and no frames averaging leads to the best performance in removing noise from the noisy speech.展开更多
In this paper, a linear moving average recursive filtering technique is proposed to reduce the peak-to-average power ratio (PAR) of orthogonal frequency division multiplexing (OFDM) signals. The proposed low complexit...In this paper, a linear moving average recursive filtering technique is proposed to reduce the peak-to-average power ratio (PAR) of orthogonal frequency division multiplexing (OFDM) signals. The proposed low complexity technique is analyzed in an oversampled OFDM system and a simple distribution approximation of the oversampled and linearly filtered OFDM signals is also proposed. Corresponding time domain linear equalizers are developed to recover originally transmitted data symbols. Through extensive computer simulations, effects of the new filtering technique on the oversampled OFDM peak-to-average power ratio (PAR), power spectral density (PSD) and corresponding linear equalizers on the frequency selective Rayleigh fading channel transmission symbol-error-rate (SER) performance are investigated. The newly proposed recursive filtering scheme results in attractive PAR reduction, requires no extra fast Fourier transform/inverse fast Fourier transform (FFT/IFFT) operations, refrains from transmitting any side information, and reduces out-of-band radiation. Also, corresponding linear receivers are shown to perform very close to their frequency domain counterparts.展开更多
Oversampling is commonly encountered in orthogonal frequency division multiplexing (OFDM) systems to ease various performance characteristics. In this paper, we investigate the performance and complexity of one tap ze...Oversampling is commonly encountered in orthogonal frequency division multiplexing (OFDM) systems to ease various performance characteristics. In this paper, we investigate the performance and complexity of one tap zero-forcing (ZF) and minimum mean-square error (MMSE) equalizers in oversampled OFDM systems. Theoretical analysis and simulation results show that oversampling not only reduces the noise at equalizer output but also helps mitigate ill effects of spectral nulls. One tap equalizers therefore yield improved symbol-error-rate (SER) performance with the increase in oversampling rate, but at the expense of increased system bandwidth and modest complexity requirements.展开更多
文章根据载货汽车的特点对其模型进行了简化,建立了十一自由度的多刚体系统动力学模型;以卡尔丹角描述载货汽车多刚体系统的姿态,运用多刚体系统动力学建模方法,建立了载货汽车十一自由度平顺性动力学模型及其动力学方程;激励分析中考...文章根据载货汽车的特点对其模型进行了简化,建立了十一自由度的多刚体系统动力学模型;以卡尔丹角描述载货汽车多刚体系统的姿态,运用多刚体系统动力学建模方法,建立了载货汽车十一自由度平顺性动力学模型及其动力学方程;激励分析中考虑了轮胎径向跳动的影响,采用逆快速傅里叶变换(inverse fast Fourier transform,IFFT)法建立了四轮相关路面随机输入时域模型;在此基础上,利用Matlab的GUI模块开发了载货汽车平顺性时域仿真系统,并以某型号载货汽车为例进行了平顺性时域仿真;最后,通过载货汽车平顺性实验,验证了该系统的仿真结果是准确可靠的。该系统实现了载货汽车多刚体系统的参数化建模与仿真,能有效地对载货汽车平顺性进行性能预测和评估。展开更多
文摘Spectral subtraction is used in this research as a method to remove noise from noisy speech signals in the frequency domain. This method consists of computing the spectrum of the noisy speech using the Fast Fourier Transform (FFT) and subtracting the average magnitude of the noise spectrum from the noisy speech spectrum. We applied spectral subtraction to the speech signal “Real graph”. A digital audio recorder system embedded in a personal computer was used to sample the speech signal “Real graph” to which we digitally added vacuum cleaner noise. The noise removal algorithm was implemented using Matlab software by storing the noisy speech data into Hanning time-widowed half-overlapped data buffers, computing the corresponding spectrums using the FFT, removing the noise from the noisy speech, and reconstructing the speech back into the time domain using the inverse Fast Fourier Transform (IFFT). The performance of the algorithm was evaluated by calculating the Speech to Noise Ratio (SNR). Frame averaging was introduced as an optional technique that could improve the SNR. Seventeen different configurations with various lengths of the Hanning time windows, various degrees of data buffers overlapping, and various numbers of frames to be averaged were investigated in view of improving the SNR. Results showed that using one-fourth overlapped data buffers with 128 points Hanning windows and no frames averaging leads to the best performance in removing noise from the noisy speech.
文摘In this paper, a linear moving average recursive filtering technique is proposed to reduce the peak-to-average power ratio (PAR) of orthogonal frequency division multiplexing (OFDM) signals. The proposed low complexity technique is analyzed in an oversampled OFDM system and a simple distribution approximation of the oversampled and linearly filtered OFDM signals is also proposed. Corresponding time domain linear equalizers are developed to recover originally transmitted data symbols. Through extensive computer simulations, effects of the new filtering technique on the oversampled OFDM peak-to-average power ratio (PAR), power spectral density (PSD) and corresponding linear equalizers on the frequency selective Rayleigh fading channel transmission symbol-error-rate (SER) performance are investigated. The newly proposed recursive filtering scheme results in attractive PAR reduction, requires no extra fast Fourier transform/inverse fast Fourier transform (FFT/IFFT) operations, refrains from transmitting any side information, and reduces out-of-band radiation. Also, corresponding linear receivers are shown to perform very close to their frequency domain counterparts.
文摘Oversampling is commonly encountered in orthogonal frequency division multiplexing (OFDM) systems to ease various performance characteristics. In this paper, we investigate the performance and complexity of one tap zero-forcing (ZF) and minimum mean-square error (MMSE) equalizers in oversampled OFDM systems. Theoretical analysis and simulation results show that oversampling not only reduces the noise at equalizer output but also helps mitigate ill effects of spectral nulls. One tap equalizers therefore yield improved symbol-error-rate (SER) performance with the increase in oversampling rate, but at the expense of increased system bandwidth and modest complexity requirements.
文摘文章根据载货汽车的特点对其模型进行了简化,建立了十一自由度的多刚体系统动力学模型;以卡尔丹角描述载货汽车多刚体系统的姿态,运用多刚体系统动力学建模方法,建立了载货汽车十一自由度平顺性动力学模型及其动力学方程;激励分析中考虑了轮胎径向跳动的影响,采用逆快速傅里叶变换(inverse fast Fourier transform,IFFT)法建立了四轮相关路面随机输入时域模型;在此基础上,利用Matlab的GUI模块开发了载货汽车平顺性时域仿真系统,并以某型号载货汽车为例进行了平顺性时域仿真;最后,通过载货汽车平顺性实验,验证了该系统的仿真结果是准确可靠的。该系统实现了载货汽车多刚体系统的参数化建模与仿真,能有效地对载货汽车平顺性进行性能预测和评估。
