Channel Behavior(渠道行为)研究综述
Channel Behavior 渠道行为 - The fabricated OFET devices show typical p-channel behavior. [1] Adaptive error control adaptively changes error correction code (ECC) based on the channel behavior that is observed through the packet error rate (PER) in the recent previous transmissions. [2] Channel behavior is related to the existing channel processes that lead to frequent changes in the water and sediment flow pattern of a river. [3] Additionally, it has managerial implications for retailing: cross-channel behavior in this category is largely triggered by uncertainty-related factors. [4] This paper reports the ac and noise characteristics of JN-FETs with different gate lengths and shows that due to the improved electrostatic control and better immunity to short-channel effects, several key quantities such as the drain/gate excess noise factors and correlation coefficient demonstrate classical long-channel behavior for channel lengths as small as 16 nm. [5] The bottom-gate, top-contact OFETs based on TAPTVT and BZCTVT exhibited only p-channel behavior with hole mobility of 4. [6] Analysis of the present study revealed a high frequency of backchannel behavior by the host occurs in both languages. [7] (ii) A simulation study is conducted for a comparative analysis of various modulation schemes, leveraging the validated GC-channel behavior. [8] These two polymers show dominant n- and p-channel behavior in organic field-effect transistors. [9] The single-channel behavior of the human body is accommodated with a novel, simple yet robust single-wire signaling technique that is called Pulsed-Index Communication (PIC). [10] Here, we used a combination of approaches to try to understand the role of the ankyrin repeat domain (ARD) in channel behavior. [11] The optimized NiO TFT exhibits outstanding p-channel behavior, including a high hole mobility of 6. [12] These techniques, for the most part, arise from information-theoretic measures or otherwise associated with the channel behavior, which does not necessarily model the coding being employed. [13] , Single-Input Multiple-Output OFDM (SIMO-OFDM) systems, where we show that SIMO OSBCE can be designed in different variations based on the channel behavior as a function of the Euclidean distance between the symbols used in the OSBCE structure. [14] This paper continues a line of work studying intermediate models in which the channel behavior can depend partially on the transmitted codeword. [15] Currently, consumers display what is known as omnichannel behavior: the combined use of digital and physical channels providing them with multiple points of contact with firms. [16] Currently, one of the most influential omnichannel behaviors is research shopping in its two predominant forms: webrooming and showrooming. [17] Confidence is stressed as a key variable in omnichannel behavior. [18] 7N barrier layer, and a 3-nm Al2O3 gate dielectric, the gate length (制造的 OFET 器件显示出典型的 p 沟道行为。 [1] 自适应错误控制根据在最近的先前传输中通过分组错误率 (PER) 观察到的信道行为自适应地更改纠错码 (ECC)。 [2] 河道行为与现有河道过程有关，导致河流的水和泥沙流型发生频繁变化。 [3] 此外，它对零售业具有管理意义：这一类别的跨渠道行为主要是由与不确定性相关的因素触发的。 [4] 本文报告了具有不同栅极长度的 JN-FET 的交流和噪声特性，并表明由于改进的静电控制和更好的短沟道效应抗扰度，漏极/栅极过量噪声因子和相关系数等几个关键量表明通道长度小至 16 nm 的经典长通道行为。 [5] 基于 TAPTVT 和 BZCTVT 的底栅、顶接触 OFET 仅表现出 p 沟道行为，空穴迁移率为 4。 [6] 对本研究的分析表明，主机的反向通道行为在两种语言中都发生了很高的频率。 [7] (ii) 利用经过验证的 GC 通道行为，对各种调制方案进行比较分析的模拟研究。 [8] 这两种聚合物在有机场效应晶体管中显示出主要的 n 沟道和 p 沟道行为。 [9] 人体的单通道行为由一种称为脉冲索引通信 (PIC) 的新颖、简单但强大的单线信号技术来适应。 [10] 在这里，我们使用了多种方法来尝试了解锚蛋白重复域 (ARD) 在通道行为中的作用。 [11] 优化的 NiO TFT 表现出出色的 p 沟道行为，包括 6 的高空穴迁移率。 [12] 这些技术大部分来自信息论测量或与信道行为相关的其他方法，这不一定对所采用的编码进行建模。 [13] , 单输入多输出 OFDM (SIMO-OFDM) 系统，我们展示了 SIMO OSBCE 可以根据作为 OSBCE 结构中使用的符号之间的欧几里得距离的函数的信道行为设计为不同的变体。 [14] 本文继续研究中间模型，其中信道行为可能部分取决于传输的码字。 [15] 目前，消费者表现出所谓的全渠道行为：数字和实体渠道的结合使用为他们提供了与公司的多个联系点。 [16] 目前，最有影响力的全渠道行为之一是以两种主要形式研究购物：网络展示和陈列室。 [17] 信心被强调为全渠道行为的关键变量。 [18] 7</sub>N 势垒层，以及 3-nm Al<sub>2</sub>O<sub>3</sub> 栅极电介质，栅极长度 (<inline-formula> <tex-math notation= "LaTeX">${L}_{\text {G}}$ </tex-math></inline-formula>) 作为从长通道行为到短通道行为的过渡点被发现是200 纳米。 [19] 此外，还显示了所呈现设备的短通道行为的改进。 [20] 本文主要关注基于中心电位的自然长度来估计器件的确切短通道行为。 [21] 在这里，我们使用了多种方法来尝试了解锚蛋白重复结构域 (ARD) 在通道行为中的作用。 [22] 特别是，提出了一种基于 CS 的信道脉冲响应估计方法，该方法可以识别信道行为中的损伤。 [23] 可以得出结论，对于某些链路，与 off-B/no-B 场景相比，B-to-B 信道的信道行为发生了显着变化。 [24] 了解信道行为将有助于链路设计人员应用适当的缓解机制，如均衡器或 FEC。 [25] 阈值处的极性灵敏度定义为响应于两个三相脉冲中的每一个测量的单通道行为阈值的差异，其中中心高幅度相位是阴极或阳极。 [26]
Short Channel Behavior 短信道行为
However, the magnetic field has no considerable effect on the threshold voltage neither the short channel behavior for the proposed Si GAA NWFET even with increasing the biasing values and at different device parameters. [1] Multigate FET like FINFET and CNTFET (carbon Nano tube field effect transistor) are the devices to replace that because of improved drive strength and short channel behavior. [2] By comparing off-state leakage current, short channel behavior and effective capacitance (Ceff) for both schemes, we show that BDI could potentially provide: 1) good immunity of sub-channel leakage due to process variation (from parasitic "fat-Fin" which is unique in Nanosheet structure); 2) power-performance co-optimization. [3]然而，磁场对阈值电压和所提出的 Si GAA NWFET 的短沟道行为都没有显着影响，即使在增加偏置值和不同器件参数的情况下也是如此。 [1] 像 FINFET 和 CNTFET（碳纳米管场效应晶体管）这样的多栅极 FET 是替代它的器件，因为它提高了驱动强度和短沟道行为。 [2] 通过比较两种方案的关闭状态泄漏电流、短沟道行为和有效电容 (Ceff)，我们表明 BDI 可能提供：1) 由于工艺变化（来自寄生“胖鳍”）引起的子沟道泄漏的良好抗扰性在纳米片结构中是独一无二的）； 2) 电源性能协同优化。 [3]
Constant Channel Behavior 恒定通道行为
Magnetic induction (MI) communication is a promising candidate thanks to several unique features such as small transmission delay, constant channel behavior and high bandwidth. [1] In recent research on 3D underwater wireless sensor network (UWSN), magnetic induction communication is a promising candidate, thanks to several unique features, such as small transmission delay, constant channel behavior, and adequate long communication range. [2]磁感应 (MI) 通信是一个很有前途的候选者，这要归功于一些独特的特性，例如传输延迟小、信道行为恒定和带宽高。 [1] 在最近对 3D 水下无线传感器网络 (UWSN) 的研究中，磁感应通信是一个很有前途的候选者，这要归功于几个独特的特性，例如传输延迟小、信道行为恒定和足够长的通信范围。 [2]
Communication Channel Behavior 沟通渠道行为
In order to design high throughput and efficient signal communication schemes for these emerging scenarios, a deep understanding of communication channel behavior is required. [1] Successful data transmission depends on several parameters, such as delay, communication channel behavior, and packet loss. [2]为了为这些新兴场景设计高吞吐量和高效的信号通信方案，需要对通信信道行为有深入的了解。 [1] 成功的数据传输取决于几个参数，例如延迟、通信通道行为和数据包丢失。 [2]
Single Channel Behavior 单通道行为
Here, to search for physiological mechanisms controlling epithelial Na+ channel (ENaC)‐like channels, we utilized leukemia K562 cells as a unique model to examine single channel behavior in a whole‐cell patch‐clamp experiments. [1] Nowadays, in spite of high performance of users’ single channel behavior computing, it is still great challenge to understand users’ intention accurately from their multimodal behaviors. [2]在这里，为了寻找控制上皮钠离子通道 (ENaC) 样通道的生理机制，我们利用白血病 K562 细胞作为一种独特的模型来检查全细胞膜片钳实验中的单通道行为。 [1] 如今，尽管用户的单通道行为计算性能很高，但从用户的多模态行为中准确理解用户意图仍然是一个巨大的挑战。 [2]