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Dimensional-parameters-of-acoustic-signals-is-esti
- 估计声信号二维参数的免疫量子克隆算法Dimensional parameters of acoustic signals is estimated quantum immune clone algorithm-Dimensional parameters of acoustic signals is estimated quantum immune clone algorithm
acoustic2d
- 声波在二维各向同性介质中的传播波场，包括波长快照和在地面接收到的波形图。-Acoustic waves in two-dimensional wave propagation in isotropic media field, including the wavelength and on the ground receives a snapshot of the waveform.
Tank
- LMBP算法的罐底腐蚀声发射信号模式识别Tank bottom corrosion LMBP algorithm pattern recognition of acoustic emission signals-Tank bottom corrosion LMBP algorithm pattern recognition of acoustic emission signals
RP094_VOL.5-2234
- artithe intelligent virtual environment in an artificial fish of virtual auditory system is designed in this paper. Firstly, the model of artificial fish of auditory system in intelligent virtual environment (IVE) is built. Secondly, two-laye
Source-Localization-in-UWSAN
- 文章针对低信噪比下的水下目标定位问题，建立了水下无线传感器阵列网络，该结构包括多个分布式声传感器阵列，它适应于多模态信号处理，既可以利用目标的方位信息，又可以用能量信息。文中提出了用每个阵列接收到的信号能量作为参量完成目标定位并推导了基于能量的最大似然比目标定位方法。数值仿真表明：基于该结构的能量似然函数定位方法，可以有效估计目标的位置。并且比单阵元网络的定位性能和信息传输率上有了较大的提高， 尤其是在低信噪比下情况下，可以大大减小估计的方差。-With novel underwater wir
189-199
- As the compact design of a muffler system within a constrained environment of a existing machine room becomes obligatory, it also becomes essential to maximize the acoustic performance of mufflers under space constraints. In this paper, the sha
matlab
- 用四元十字阵做被动声定位算法设计，现在是用matlab神经网络工具箱构建RBF神经网络然后仿真显示图形-With a four-element Array do passive acoustic localization algorithm design, now using matlab neural network toolbox and then build on RBF neural network simulation display graphics
RBF-neural-network
- 用四元十字阵做被动声定位算法设计，现在是用matlab神经网络工具箱构建RBF神经网络然后仿真显示图形-With a four-element Array do passive acoustic localization algorithm design, now using matlab neural network toolbox and then build on RBF neural network simulation display graphics
ANN-using-Acoustic-features
- extraction of acoustic features for the pattern recognition using AI
DeepLearnToolbox_CNN_lzbV3.0
- CNN - 主程序 参考文献: [1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006 [2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998 [3] https://github.com/rasmusbergpalm/DeepLearnToolbox 作者：陆振波 电子
ku223
- 基于chebyshev的水声信号分析，ldpc码的编解码实现，MinkowskiMethod算法 。- Based chebyshev underwater acoustic signal analysis, Codec ldpc code implementation MinkowskiMethod algorithm.
acwbu
- 基于chebyshev的水声信号分析，sar图像去噪的几种新的方法，详细画出了时域和频域的相关图。- Based chebyshev underwater acoustic signal analysis, Several new methods sar image denoising, Correlation diagram shown in detail the time domain and frequency domain.
de545
- Including single sideband, double sideband, suppressed carrier and quadruple, Including the generalized cross-correlation function GCC time delay estimation, Based chebyshev underwater acoustic signal analysis.
AcousticChannelSimulator
- 计算海洋声学 深海声道模型 射线声学方法(Computational ocean acoustic deep-sea channel model)