標(biāo)題: Titlebook: Neuromorphic Computing and Beyond; Parallel, Approximat Khaled Salah Mohamed Book 2020 Springer Nature Switzerland AG 2020 cognitive comput [打印本頁] 作者: 本義 時(shí)間: 2025-3-21 19:43
書目名稱Neuromorphic Computing and Beyond影響因子(影響力)
書目名稱Neuromorphic Computing and Beyond影響因子(影響力)學(xué)科排名
書目名稱Neuromorphic Computing and Beyond網(wǎng)絡(luò)公開度
書目名稱Neuromorphic Computing and Beyond網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Neuromorphic Computing and Beyond被引頻次
書目名稱Neuromorphic Computing and Beyond被引頻次學(xué)科排名
書目名稱Neuromorphic Computing and Beyond年度引用
書目名稱Neuromorphic Computing and Beyond年度引用學(xué)科排名
書目名稱Neuromorphic Computing and Beyond讀者反饋
書目名稱Neuromorphic Computing and Beyond讀者反饋學(xué)科排名
作者: 開花期女 時(shí)間: 2025-3-21 23:13 作者: athlete’s-foot 時(shí)間: 2025-3-22 01:13
Cloud, Fog, and Edge Computing,Cloud computing virtualizes the computing, storage, and band width. Thus, it reduces the deployment cost for software services and provides support for industrialization.作者: Semblance 時(shí)間: 2025-3-22 06:43
Conclusions,In this book, the traditional computing concepts are introduced. The main walls and the need for new trends in computing are highlighted. New trends are needed to enhance computing capability as Moore’s law is slowing down, but the demand for computing keeps increasing.作者: 傲慢人 時(shí)間: 2025-3-22 11:24
http://image.papertrans.cn/n/image/664238.jpg作者: gratify 時(shí)間: 2025-3-22 14:16 作者: Amendment 時(shí)間: 2025-3-22 17:29 作者: Consensus 時(shí)間: 2025-3-22 22:19
Book 2020el, In Memory, and Quantum Computing.? The author shows how these paradigms are used to enhance computing capability as developers face the practical and physical limitations of scaling, while the demand for computing power keeps increasing.? The discussion includes a state-of-the-art overview and t作者: staging 時(shí)間: 2025-3-23 01:58
Parallel, In Memory, and Quantum Computing concepts, in a ma.This book discusses and compares several new trends that can be used to overcome Moore’s law limitations, including Neuromorphic, Approximate, Parallel, In Memory, and Quantum Computing.? The author shows how these paradigms are used to en作者: 蜈蚣 時(shí)間: 2025-3-23 08:26 作者: 不如屎殼郎 時(shí)間: 2025-3-23 11:46 作者: 抗原 時(shí)間: 2025-3-23 14:24 作者: 通便 時(shí)間: 2025-3-23 21:31
Reconfigurable and Heterogeneous Computing,vices are usually controlled by a microprocessor that executes the instructions stored on a read-only memory (ROM) chip. The software for the embedded system is called firmware. Embedded systems are also known as real-time systems since they respond to an input or event and produce the result within a guaranteed time period [1].作者: 剛毅 時(shí)間: 2025-3-24 00:51
Deep Learning and Cognitive Computing: Pillars and Ladders,s in difficult machine learning problems such as image or object recognition, speech recognition and machine language translation. Now machine learning is everywhere. Facebook as an example, machine learning in search, face tagging, advertisement, and news feed.作者: Extricate 時(shí)間: 2025-3-24 02:27
Approximate Computing: Towards Ultra-Low-Power Systems Design,accurate result to save resources, memory, run-time, and energy. The motivation behind this is that some applications are computing their results more accurately than needed, so they waste resources. So, it trades off between accuracy in computation or acceptable quality of results and resources [1]作者: 昏睡中 時(shí)間: 2025-3-24 07:49 作者: Highbrow 時(shí)間: 2025-3-24 14:16
An Introduction: New Trends in Computing,manufacturing cost. As Gordon Moore predicted in his seminal paper, reducing the feature size also allows chip area to be decreased, improving production, and thereby reducing cost per function. The scaling laws showed that improved device and ultimately processor speed could be achieved through dim作者: 上釉彩 時(shí)間: 2025-3-24 17:22 作者: 推遲 時(shí)間: 2025-3-24 22:25 作者: 貝雷帽 時(shí)間: 2025-3-25 02:42
Deep Learning and Cognitive Computing: Pillars and Ladders, machine learning that deals with algorithms inspired by the structure and function of the brain. Machine learning is a subset of artificial intelligence as shown in Fig. 4.1. Deep neural networks (DNNs) are a family of neuromorphic computing architectures that have recently made substantial advance作者: corn732 時(shí)間: 2025-3-25 03:31 作者: Terrace 時(shí)間: 2025-3-25 10:56 作者: Exuberance 時(shí)間: 2025-3-25 11:41
Quantum Computing and DNA Computing: Beyond Conventional Approaches,n Moore,” and (3) “Beyond CMOS as depicted in Table 7.1. The “More Moore” domainis traditionally dealing with technologies related to the silicon-based CMOS. The “More than Moore” domain encompasses the engineering of complex systems that can combine, by heterogeneous integration techniques (in SoC 作者: faddish 時(shí)間: 2025-3-25 18:03 作者: 透明 時(shí)間: 2025-3-25 23:50 作者: CROAK 時(shí)間: 2025-3-26 02:43 作者: 偽善 時(shí)間: 2025-3-26 06:39 作者: micronutrients 時(shí)間: 2025-3-26 10:50
Parallel Computing: OpenMP, MPI, and CUDA, threshold, and thus supply voltages no longer scale down each generation. Hence, to leverage the additional transistors, designers reduce clock frequency and invest the power headroom to activate twice as many cores. Because of the quadratic relationship between power and voltage, a small voltage/f作者: Ophthalmologist 時(shí)間: 2025-3-26 16:02 作者: athlete’s-foot 時(shí)間: 2025-3-26 17:35 作者: Definitive 時(shí)間: 2025-3-26 21:59 作者: 把…比做 時(shí)間: 2025-3-27 02:16
Khaled Salah Mohamedere stimulated by the pioneering work of Alexander et al. who recast the Evans function in a dynamical systems language. The subsequent synergy between dynamical systems and functional analysis has yielded a burst of activity and produced a unified framework for the study of stability and bifurcatio作者: COM 時(shí)間: 2025-3-27 08:25
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