Time Spectrum(时间谱)研究综述
Time Spectrum 时间谱 - The expediency of use of wavelet transformation of time realizations of a vibration signal is shown, as a result of which the received vibration signal is divided into amplitude-frequency-time spectrum, which leads to increase its informativeness. [1] To compensate that weakness, the combination of Echo Hiding in time spectrum is proposed. [2] For this purpose, a short-time spectrum is computed using the short-time Fourier transform (STFT) as a feature extraction tool in this paper. [3] In this paper, we propose a novel method of estimation of short-time spectrum for analysis of speech signals in the closed phase regions of glottal activity. [4] Together with an analysis of the spacetime spectrum, this allows us to show that the long string sector of superstring theory on AdS 3 × S 3 × T 4 for generic NS-NS flux is described by the symmetric orbifold of ( N = 4 Liouville theory ) × T 4. [5] The method is based on detecting lower side frequencies of the fictitious rotor winding harmonics in the frequency-time spectrum during the startup. [6] A special feature is the possibility to exclude certain channel ranges in a lifetime spectrum from the analysis, which may be valuable if spectra contain ”bumps”, for example due to scattered positrons in beam experiments. [7] To analyze the obtained positron annihilation lifetime spectrum and extract the lifetime components and their intensities, the Pascual software was used. [8] The detector system can record a time spectrum of the nuclear radiation simultaneously with an intensity distribution at each pixel. [9] It is shown that the spacetime spectrum, as well as the algebra of spectrum generating operators, matches precisely that of the symmetric orbifold of S3 × S1 in the large N limit. [10] Therefore, additional research is needed to design systems that bring deep learning algorithms directly on the device’s hardware and tightly intertwined with the RF components to enable real-time spectrum-driven decision-making at the physical layer. [11] The gradients of the peak on the positron annihilation lifetime spectrum for a sample annealed at 700 °C is increased compared to the as extruded sample. [12] When signal from radio source propagates through irregularity layer in the ionosphere it has fluctuations of the amplitude (scintillations) which time spectrum has power form with index α = 3. [13] Deterministic input testing signals are characterized namely by their spectral properties, which are continuous-time spectrum in case of continuous-time signals and discrete spectrum in case of discrete signals. [14] Results indicate that the barrier of PEF to CO2 is much higher than that of PETH, in spite of the higher free volume fractions and larger free volume diameters of PEF determined by rheological analysis and Positron Annihilation Lifetime Spectrum (PALS). [15] The obtained carrier lifetime spectrum can be modeled with a simple diffusion equation to determine bulk recombination lifetime and carrier mobility. [16] It is concluded that: (a) current PISN candidates, in particular SN 2007bi, are more likely the result of the collapse and explosion of massive stars below the PI limit; (b) significant asymmetry is required to reproduce the late-time spectrum of SN2007bi. [17] The composition of the respiration that is most suitable for the calculation is then selected based on its time spectrum. [18] In the method, the target vector (also known as the target polarization-space-time steering vector) is determined based on the maximum likelihood scheme, while the clutter polarization-space-time spectrum (profile) is reconstructed by using a newly developed polarimetric sparse recovery technique. [19] The proposed technique computes wavelet packet-based short-time spectrum of speech signal. [20] By using the real-time spectrum and oscilloscope, the calculation with all conversion and correction factors is derived. [21] If the data are bordered by the time spectrum, problem is even deeper. [22] It is shown that the spacetime spectrum, as well as the algebra of spectrum generating operators, matches precisely that of the symmetric orbifold of ${\rm S}^3\times \mathrm{S}^1$ in the large $N$ limit. [23]显示了使用小波变换对振动信号的时间实现的权宜之计，结果是将接收到的振动信号划分为幅频时间谱，从而增加其信息量。 [1] 为了弥补这一弱点，提出了在时间谱中结合回声隐藏。 [2] 为此，本文使用短时傅里叶变换（STFT）作为特征提取工具来计算短时谱。 [3] 在本文中，我们提出了一种新的短时频谱估计方法，用于分析声门活动闭合相位区域中的语音信号。 [4] 连同对时空谱的分析，这使我们能够证明，对于通用 NS-NS 通量，AdS 3 × S 3 × T 4 上的超弦理论的长弦扇区由 ( N = 4 刘维尔理论的对称轨道描述) × T 4。 [5] 该方法基于在启动期间检测频率-时间谱中虚拟转子绕组谐波的下侧频率。 [6] 一个特殊的功能是可以从分析中排除寿命光谱中的某些通道范围，如果光谱包含“凸起”，例如由于光束实验中的散射正电子，这可能是有价值的。 [7] 为了分析获得的正电子湮没寿命谱并提取寿命分量及其强度，使用了Pascual软件。 [8] 检测器系统可以同时记录核辐射的时间谱以及每个像素的强度分布。 [9] 结果表明，时空谱以及谱生成算子的代数在大 N 极限下与 S3 × S1 的对称轨道精确匹配。 [10] 因此，需要额外的研究来设计系统，将深度学习算法直接引入设备的硬件并与射频组件紧密结合，以实现物理层的实时频谱驱动决策。 [11] 与挤压样品相比，在 700 °C 下退火的样品的正电子湮没寿命谱峰的梯度增加了。 [12] 当来自无线电源的信号通过电离层中的不规则层传播时，它具有幅度波动（闪烁），其时间谱具有指数 α = 3 的功率形式。 [13] 确定性输入测试信号的特征在于它们的频谱特性，在连续时间信号的情况下为连续时间频谱，在离散信号的情况下为离散频谱。 [14] 结果表明，尽管通过流变分析和正电子湮没寿命谱 (PALS) 确定 PEF 的自由体积分数更高，自由体积直径更大，但 PEF 对 CO2 的阻隔性远高于 PETH。 [15] 获得的载流子寿命谱可以用一个简单的扩散方程建模，以确定体复合寿命和载流子迁移率。 [16] 得出的结论是： (a) 当前的 PISN 候选者，特别是 SN 2007bi，更有可能是 PI 极限以下的大质量恒星坍缩和爆炸的结果； (b) 再现 SN2007bi 的后期频谱需要显着的不对称性。 [17] 然后根据其时间谱选择最适合计算的呼吸成分。 [18] 该方法基于最大似然法确定目标矢量（也称为目标极化-空时转向矢量），而利用新开发的极化法重构杂波极化-时空谱（轮廓）。稀疏恢复技术。 [19] 所提出的技术计算语音信号的基于小波包的短时频谱。 [20] 通过使用实时频谱和示波器，推导出所有转换和校正因子的计算。 [21] 如果数据以时间谱为界，问题就更深了。 [22] 结果表明，时空谱以及谱生成算子的代数与大 $N$ 中 ${\rm S}^3\times \mathrm{S}^1$ 的对称轨道精确匹配限制。 [23]
linear time branching 线性时间分支
In the end, we achieve a method which can be used to compute all branching distances in the linear-time--branching-time spectrum. [1] This paper studies linear time-branching time spectrum of equivalences for interactive Markov chains (IMCs). [2] In the particular case of labelled transition systems, these equivalences range from trace equivalence to (strong) bisimilarity, and are organized in what is known as the linear time -- branching time spectrum. [3] In particular, characteristic formulae are exactly the prime and consistent ones for all the semantics in van Glabbeek's linear time-branching time spectrum. [4]最后，我们实现了一种可用于计算线性时间-分支时间谱中所有分支距离的方法。 [1] 本文研究了交互式马尔可夫链（IMC）等价的线性时间分支时间谱。 [2] 在标记转换系统的特定情况下，这些等价的范围从迹等价到（强）双相似性，并且组织在所谓的线性时间 - 分支时间谱中。 [3] nan [4]
Relaxation Time Spectrum 弛豫时间谱
The most general linear viscoelastic model – the generalized Maxwell body with continuous relaxation time spectrum – produces a consistent storage and loss modulus, as can be verified by Kramers–Kronig formulae. [1] For a range of stresses, the material shows time stress superposition suggesting the shape of the evolving relaxation time spectrum to be independent of the time as well as the stress. [2] The viscoelasticity is expressed by a dual power law relaxation time spectrum H(τ), consisting of relaxation processes at short (n1) and long (n2) tim. [3] Melt rheology was used to study the influence of reactive melt mixing and localization of MWCNTs in terms of melt viscoelastic properties and relaxation time spectrum. [4] The revealed regularity of the change in the relaxation time spectrum of T2-images reflects the degenerative process in subchondral bone with osteoarthritis. [5] Then the stretch relaxation time and corresponding critical shear rate at different temperatures for the flow regime transition were calculated via the discrete Maxwell relaxation time spectrum and Arrhenius equation. [6] The dynamic susceptibility of concentrated ferrofluids of magnetite-kerosene type is studied experimentally to clarify the effect of interparticle interactions on the magnetization reversal dynamics and the ferrofluid relaxation time spectrum. [7] The revealed regularity of the change in the relaxation time spectrum of T2-images reflects the degenerative process in subchondral bone with osteoarthritis. [8]最通用的线性粘弹性模型——具有连续弛豫时间谱的广义麦克斯韦体——产生一致的储能模量和损耗模量，这可以通过 Kramers-Kronig 公式进行验证。 [1] 对于一系列应力，该材料显示出时间应力叠加，表明演变的弛豫时间谱的形状与时间和应力无关。 [2] nan [3] nan [4] nan [5] nan [6] nan [7] nan [8]
Branching Time Spectrum 分支时间谱
This paper studies linear time-branching time spectrum of equivalences for interactive Markov chains (IMCs). [1] In the particular case of labelled transition systems, these equivalences range from trace equivalence to (strong) bisimilarity, and are organized in what is known as the linear time -- branching time spectrum. [2] In particular, characteristic formulae are exactly the prime and consistent ones for all the semantics in van Glabbeek's linear time-branching time spectrum. [3]本文研究了交互式马尔可夫链（IMC）等价的线性时间分支时间谱。 [1] 在标记转换系统的特定情况下，这些等价的范围从迹等价到（强）双相似性，并且组织在所谓的线性时间 - 分支时间谱中。 [2] nan [3]
Real Time Spectrum 实时频谱
Running discrete Fourier transform (running DFT) is being used to overcome the drawbacks of ping pong buffer technique by employing fast Fourier transform (FFT) for real time spectrum analyzer, However, the major drawback of existing MAC or CORDIC (CO-ordinate Rotational DIgital Computer) based computation of running DFT is error accumulation due to finite precision machine and iterative computation which deteriorate the output in long run. [1] Persistent display view available within a Real Time Spectrum Analyzer (RTSA) enables a graphical observation of the main statistical parameters of a signal. [2] The frequency domain response of ESD events is presented with the aid of real time spectrum analysis. [3]运行离散傅里叶变换 (running DFT) 被用于克服乒乓缓冲技术的缺点，通过将快速傅里叶变换 (FFT) 用于实时频谱分析仪，然而，现有 MAC 或 CORDIC (CO-ordinate Rotational DIgital) 的主要缺点基于计算机）运行 DFT 的计算是由于有限精度机器和迭代计算导致的误差累积，从长远来看会恶化输出。 [1] 实时频谱分析仪 (RTSA) 中提供的持久显示视图能够以图形方式观察信号的主要统计参数。 [2] nan [3]
time spectrum sensing 时间频谱传感
Based on compressed sensing theory and multicoset sampling architecture, the system is capable of achieving real-time spectrum sensing of 3. [1] To overcome the challenges of the real-time spectrum sensing requirement in the dynamical noise level environment, a Savitzky-Golay smoothing method based on Welch periodogram (WS-G) is proposed for spectrum sensing in cognitive radio. [2] We present S3, a real-time spectrum sensing and analyzing method, in which a smartphone is adopted as the upper computer to send instructions to a master control module of Raspberry Pi, and the master control module drives a Software Defined Radio (SDR) based spectrum sensing module. [3] This chapter provides an evaluation of the HARPA RTE mechanism for a real-time spectrum sensing application. [4]该系统基于压缩感知理论和多集合采样架构，能够实现3.0的实时频谱感知。 [1] 为了克服动态噪声水平环境下实时频谱感知需求的挑战，提出了一种基于韦尔奇周期图（WS-G）的Savitzky-Golay平滑方法用于认知无线电中的频谱感知。 [2] 我们提出了S3，一种实时频谱感知和分析方法，采用智能手机作为上位机向树莓派主控模块发送指令，主控模块驱动基于软件定义无线电(SDR)频谱传感模块。 [3] 本章提供了用于实时频谱感知应用的 HARPA RTE 机制的评估。 [4]
time spectrum analyzer 时间频谱分析仪
Running discrete Fourier transform (running DFT) is being used to overcome the drawbacks of ping pong buffer technique by employing fast Fourier transform (FFT) for real time spectrum analyzer, However, the major drawback of existing MAC or CORDIC (CO-ordinate Rotational DIgital Computer) based computation of running DFT is error accumulation due to finite precision machine and iterative computation which deteriorate the output in long run. [1] Persistent display view available within a Real Time Spectrum Analyzer (RTSA) enables a graphical observation of the main statistical parameters of a signal. [2] 11ac communication standard was achieved by applying the complementary cumulative distribution function mode of a real - time spectrum analyzer connected to a laptop. [3] The first one is based on weighing of the maximum power channel measured in the frequency domain and the second one uses the complementary cumulative distribution function (CCDF) acquisition mode of a real-time spectrum analyzer. [4]运行离散傅里叶变换 (running DFT) 被用于克服乒乓缓冲技术的缺点，通过将快速傅里叶变换 (FFT) 用于实时频谱分析仪，然而，现有 MAC 或 CORDIC (CO-ordinate Rotational DIgital) 的主要缺点基于计算机）运行 DFT 的计算是由于有限精度机器和迭代计算导致的误差累积，从长远来看会恶化输出。 [1] 实时频谱分析仪 (RTSA) 中提供的持久显示视图能够以图形方式观察信号的主要统计参数。 [2] 11ac 通信标准是通过应用连接到笔记本电脑的实时频谱分析仪的互补累积分布函数模式来实现的。 [3] 第一个是基于频域测量的最大功率信道的加权，第二个是使用实时频谱分析仪的互补累积分布函数 (CCDF) 采集模式。 [4]
time spectrum estimation 时间谱估计
This paper introduces a Wiener filtering method based on short time spectrum estimation which is implemented in frequency domain and applied to process seismic signals of high frequency. [1] As the experimental results show, the proposed framework consisting of shorttime spectrum estimation, double feature, and RF, can recognize a wide range of animal sounds and still remains a recognition rate over 80% even under 0dB SNR. [2]本文介绍了一种基于短时谱估计的维纳滤波方法，该方法在频域实现，用于处理高频地震信号。 [1] 实验结果表明，所提出的由短时谱估计、双特征和射频组成的框架可以识别范围广泛的动物声音，即使在 0dB SNR 下仍能保持 80% 以上的识别率。 [2]