In this paper, we focus on the design of irregular QC-LDPC code based multi-level coded modulation(MLCM) scheme by jointly optimizing the component code rate and the degree distribution of the irregular QC-LDPC compon...In this paper, we focus on the design of irregular QC-LDPC code based multi-level coded modulation(MLCM) scheme by jointly optimizing the component code rate and the degree distribution of the irregular QC-LDPC component code. Firstly, the sub-channel capacities of MLCM systems is analyzed and discussed, based on which the optimal component code rate can be obtained. Secondly, an extrinsic information transfer chart based two-stage searching algorithm is proposed to find the good irregular QC-LDPC code ensembles with optimal component code rates for their corresponding sub-channels. Finally, by constructing the irregular QC-LDPC component codes from the designed ensembles with the aim of possibly enlarging the girth and reducing the number of the shortest cycles, the designed irregular QC-LDPC code based 16QAM and 64QAM MLCM systems can achieve 0.4 dB and 1.2 dB net coding gain, respectively, compared with the recently proposed regular QC-LDPC code based 16QAM and 64QAM MLCM systems.展开更多
The sub-land/sub-pit affects the characteristic of the tracking error signal which is generated by the conventional differential phase detection （DPD） method in the signal waveform modulation multi-level （SWML） re...The sub-land/sub-pit affects the characteristic of the tracking error signal which is generated by the conventional differential phase detection （DPD） method in the signal waveform modulation multi-level （SWML） read-only disc. To solve this problem, this paper proposes a new tracking error detection method using amplitude difference. Based on the diffraction theory, the amplitude difference is proportional to the tracking error and is feasible to be used for obtaining the off-track information. The experimental system of the amplitude difference detection method is developed. The experimental results show that the tracking error signal derived from the new method has better performance in uniformity and signal-to-noise ratio than that derived from the conventional DPD method in the SWML read-only disc.展开更多
In this paper, we describe an improved adaptive partial response maximum likelihood （PRML） method combining modulation code tbr signal waveform modulation multi-level disc. This improved adaptive PRML method employs...In this paper, we describe an improved adaptive partial response maximum likelihood （PRML） method combining modulation code tbr signal waveform modulation multi-level disc. This improved adaptive PRML method employs partial response equalizer and adaptive viterbi detector combining modulation code. Compared with the traditional adaptive PRML detector, the improved PRML detector additionally employs illogical sequence detector and corrector. Illogical sequence detector and corrector can aw）id the appearance of illogical sequences effectively, which do not follow the law of modulation code for signal waveform modulation multi-level disc, and obtain the correct sequences. We implement the improved PRML detector using a DSP and an FPGA chip. The experimental results show good performance. The higher efficient and lower complexity can be obtained by using the improved PRML method than by using the previous PRML method. Meanwhile, resource utilization of the improved PRML detector is not changed, but the bit error rate （BER） is reduced by more than 20%.展开更多
A novel read channel for signal waveform modulation multi-level disc is presented in this paper. This read channel employs timing recovery system and partial response maximum likelihood detector. Compared to the previ...A novel read channel for signal waveform modulation multi-level disc is presented in this paper. This read channel employs timing recovery system and partial response maximum likelihood detector. Compared to the previous read channel composed of level detection and run-length detection, the present read channel shows superiority in capacity increase and robust performance. Especially, relying on the partial response maximum likelihood detection, lower bit error rate can be obtained.展开更多
A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of ...A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore,the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship,suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.展开更多
为了解决无人机航拍图片玉米植株中心检测所面临的诸多挑战,包括植株遮挡、形态多样、光照变化以及视觉混淆等问题,提升检测精度和模型的鲁棒性,开发了一种基于YOLO-TSCAS(YOLO with triplet-attention,saliencyadaptive,and centroid a...为了解决无人机航拍图片玉米植株中心检测所面临的诸多挑战,包括植株遮挡、形态多样、光照变化以及视觉混淆等问题,提升检测精度和模型的鲁棒性,开发了一种基于YOLO-TSCAS(YOLO with triplet-attention,saliencyadaptive,and centroid awareness for scenes)模型的玉米植株中心检测算法。该算法通过三重注意力模块、显著性裁剪混合数据增强方法、自适应池化技术和选择性多单元激活函数等技术手段,有效提高了检测精度和鲁棒性。采用三重注意力模块解决目标遮挡和视觉混淆问题,使模型能够更好地关注植株中心区域。采用显著性裁剪混合数据增强方法,在训练过程中引入不同的环境和光照变化,增强了模型对复杂场景的适应能力。结合自适应池化技术提高空间分辨率,有助于捕捉更精细的特征信息,提高检测的准确性。采用选择性多单元激活函数进一步增强了网络的学习能力,使模型能够更好地适应各种场景下的植株中心检测任务。实验结果表明,与现有的YOLOX算法相比,YOLO-TSCAS算法在平均准确率和平均F1值上分别提高了22.73个百分点和0.255,并且平均对数漏检率也显著降低了0.35。与其他流行的检测模型相比,在两类植株中心目标检测精度上也取得了最佳效果。展开更多
经典AOD-Net(All in One Dehazing Network)去雾后的图像存在细节清晰度不足、明暗反差过大和画面昏暗等问题。为了解决这些图像去雾问题,提出一种在AOD-Net基础上改进的多尺度算法。改进的网络结构采用深度可分离卷积替换传统卷积方式...经典AOD-Net(All in One Dehazing Network)去雾后的图像存在细节清晰度不足、明暗反差过大和画面昏暗等问题。为了解决这些图像去雾问题,提出一种在AOD-Net基础上改进的多尺度算法。改进的网络结构采用深度可分离卷积替换传统卷积方式,减少了冗余参数量,加快了计算速度并有效地减少了模型的内存占用量,从而提高了算法去雾效率;同时采用多尺度结构在不同尺度上对雾图进行分析和处理,更好地捕捉图像的细节信息,提升了网络对图像细节的处理能力,解决了原算法去雾时存在的细节模糊问题;最后在网络结构中加入金字塔池化模块,用于整合图像不同区域的上下文信息,扩展了网络的感知范围,从而提高网络模型获取有雾图像全局信息的能力,进而改善图像色调失真、细节丢失等问题。此外,引入一个低照度增强模块,通过明确预测噪声实现去噪的目标,从而恢复曝光不足的图像。在低光去雾图像中,峰值信噪比(PSNR)和结构相似性(SSIM)指标均有显著提升,处理后的图片具有更高的整体自然度。实验结果表明:与经典AOD-Net去雾的结果相比,改进算法能够更好地恢复图像的细节和结构,使得去雾后的图像更自然,饱和度和对比度也更加平衡;在RESIDE的SOTS数据集中的室外和室内场景,相较于经典AOD-Net,改进算法的PSNR分别提升了4.5593 dB和4.0656 dB,SSIM分别提升了0.0476和0.0874。展开更多
基金supported by National Natural Science Foundation of China(No.61571061)
文摘In this paper, we focus on the design of irregular QC-LDPC code based multi-level coded modulation(MLCM) scheme by jointly optimizing the component code rate and the degree distribution of the irregular QC-LDPC component code. Firstly, the sub-channel capacities of MLCM systems is analyzed and discussed, based on which the optimal component code rate can be obtained. Secondly, an extrinsic information transfer chart based two-stage searching algorithm is proposed to find the good irregular QC-LDPC code ensembles with optimal component code rates for their corresponding sub-channels. Finally, by constructing the irregular QC-LDPC component codes from the designed ensembles with the aim of possibly enlarging the girth and reducing the number of the shortest cycles, the designed irregular QC-LDPC code based 16QAM and 64QAM MLCM systems can achieve 0.4 dB and 1.2 dB net coding gain, respectively, compared with the recently proposed regular QC-LDPC code based 16QAM and 64QAM MLCM systems.
基金Project supported by the National Natural Science Foundation of China (Grant No. 60977005)
文摘The sub-land/sub-pit affects the characteristic of the tracking error signal which is generated by the conventional differential phase detection （DPD） method in the signal waveform modulation multi-level （SWML） read-only disc. To solve this problem, this paper proposes a new tracking error detection method using amplitude difference. Based on the diffraction theory, the amplitude difference is proportional to the tracking error and is feasible to be used for obtaining the off-track information. The experimental system of the amplitude difference detection method is developed. The experimental results show that the tracking error signal derived from the new method has better performance in uniformity and signal-to-noise ratio than that derived from the conventional DPD method in the SWML read-only disc.
基金Project supported by the National Natural Science Foundation of China(Grant No.61127010)
文摘In this paper, we describe an improved adaptive partial response maximum likelihood （PRML） method combining modulation code tbr signal waveform modulation multi-level disc. This improved adaptive PRML method employs partial response equalizer and adaptive viterbi detector combining modulation code. Compared with the traditional adaptive PRML detector, the improved PRML detector additionally employs illogical sequence detector and corrector. Illogical sequence detector and corrector can aw）id the appearance of illogical sequences effectively, which do not follow the law of modulation code for signal waveform modulation multi-level disc, and obtain the correct sequences. We implement the improved PRML detector using a DSP and an FPGA chip. The experimental results show good performance. The higher efficient and lower complexity can be obtained by using the improved PRML method than by using the previous PRML method. Meanwhile, resource utilization of the improved PRML detector is not changed, but the bit error rate （BER） is reduced by more than 20%.
文摘A novel read channel for signal waveform modulation multi-level disc is presented in this paper. This read channel employs timing recovery system and partial response maximum likelihood detector. Compared to the previous read channel composed of level detection and run-length detection, the present read channel shows superiority in capacity increase and robust performance. Especially, relying on the partial response maximum likelihood detection, lower bit error rate can be obtained.
基金Supported by the Project of Ministry of Education and Finance(No.200512)the Project of the State Key Laboratory of ocean engineering(GKZD010053-10)
文摘A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore,the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship,suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.
文摘为了解决无人机航拍图片玉米植株中心检测所面临的诸多挑战,包括植株遮挡、形态多样、光照变化以及视觉混淆等问题,提升检测精度和模型的鲁棒性,开发了一种基于YOLO-TSCAS(YOLO with triplet-attention,saliencyadaptive,and centroid awareness for scenes)模型的玉米植株中心检测算法。该算法通过三重注意力模块、显著性裁剪混合数据增强方法、自适应池化技术和选择性多单元激活函数等技术手段,有效提高了检测精度和鲁棒性。采用三重注意力模块解决目标遮挡和视觉混淆问题,使模型能够更好地关注植株中心区域。采用显著性裁剪混合数据增强方法,在训练过程中引入不同的环境和光照变化,增强了模型对复杂场景的适应能力。结合自适应池化技术提高空间分辨率,有助于捕捉更精细的特征信息,提高检测的准确性。采用选择性多单元激活函数进一步增强了网络的学习能力,使模型能够更好地适应各种场景下的植株中心检测任务。实验结果表明,与现有的YOLOX算法相比,YOLO-TSCAS算法在平均准确率和平均F1值上分别提高了22.73个百分点和0.255,并且平均对数漏检率也显著降低了0.35。与其他流行的检测模型相比,在两类植株中心目标检测精度上也取得了最佳效果。
文摘经典AOD-Net(All in One Dehazing Network)去雾后的图像存在细节清晰度不足、明暗反差过大和画面昏暗等问题。为了解决这些图像去雾问题,提出一种在AOD-Net基础上改进的多尺度算法。改进的网络结构采用深度可分离卷积替换传统卷积方式,减少了冗余参数量,加快了计算速度并有效地减少了模型的内存占用量,从而提高了算法去雾效率;同时采用多尺度结构在不同尺度上对雾图进行分析和处理,更好地捕捉图像的细节信息,提升了网络对图像细节的处理能力,解决了原算法去雾时存在的细节模糊问题;最后在网络结构中加入金字塔池化模块,用于整合图像不同区域的上下文信息,扩展了网络的感知范围,从而提高网络模型获取有雾图像全局信息的能力,进而改善图像色调失真、细节丢失等问题。此外,引入一个低照度增强模块,通过明确预测噪声实现去噪的目标,从而恢复曝光不足的图像。在低光去雾图像中,峰值信噪比(PSNR)和结构相似性(SSIM)指标均有显著提升,处理后的图片具有更高的整体自然度。实验结果表明:与经典AOD-Net去雾的结果相比,改进算法能够更好地恢复图像的细节和结构,使得去雾后的图像更自然,饱和度和对比度也更加平衡;在RESIDE的SOTS数据集中的室外和室内场景,相较于经典AOD-Net,改进算法的PSNR分别提升了4.5593 dB和4.0656 dB,SSIM分别提升了0.0476和0.0874。
