Advantages of Logarithmic Signatures in the Implementation of Crypto Primitives by Yevhen Kotukh, Hennadii Khalimov

Subjects: “…computationally complex tasks…”
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Approaching the general quantification of functional information by Robert Kudelić

“…We have also made first steps of placing functional information in a computational complexity framework, which will potentially foster algorithmics around it, especially in terms of optimality or degeneracy, and possibly even in terms of work around classes of computational complexity.…”
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Unsupervised intrusion detection model based on temporal convolutional network by LIAO Jinju, DING Jiawei, FENG Guanghui

“…However, LSTM’s sequential data processing significantly increases computational complexity and memory consumption during training. …”
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A Low Complexity Dual-Phase Alternating Scheme is Used With the PTS Method to Reduce PAPR for B5G Systems by Yung-Ping Tu, Chen-Wei Hsu

“…Simulation results show that the proposed scheme achieves better PAPR performance and computational complexity regardless of the waveform than previous well-known techniques, such as PTS, selective mapping (SLM), etc. …”
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A Network Traffic Prediction Model Based on Layered Training Graph Convolutional Network by Yulian Li, Yang Su

“…The conventional model that extracts space-correlated features of traffic flow have the problem of high computational complexity and long training time which limits the model’s application on rapid routing deployment. …”
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Sparse Regularization With Reverse Sorted Sum of Squares via an Unrolled Difference-of-Convex Approach by Takayuki Sasaki, Kazuya Hayase, Masaki Kitahara, Shunsuke Ono

“…These include developing an algorithm grounded in theory, not heuristics, reducing computational complexity, enabling the automatic determination of numerous parameters, and ensuring the number of iterations remains feasible. …”
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XTNSR: Xception-based transformer network for single image super resolution by Jagrati Talreja, Supavadee Aramvith, Takao Onoye

“…The model processes grid-like image patches effectively and reduces computational complexity by integrating a Patch Embedding layer. …”
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GS-LinYOLOv10: A drone-based model for real-time construction site safety monitoring by Yang Song, ZhenLin Chen, Hua Yang, Jifei Liao

“…These innovations reduce computational complexity while significantly improving detection accuracy. …”
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DLiGRU-X: Efficient X-Vector-Based Embeddings for Small-Footprint Keyword Spotting System by Zong-En Wu, Shao-Jung Chan, Yeshanew Ale Wubet, Kuang-Yow Lian

“…The DLiGRU-X model enhances temporal feature extraction with a LiGRU and reduces computational complexity through dilated convolution techniques. …”
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Linear Multivariate Decision Trees for Fast QTMT Partitioning in VVC by Jose N. Filipe, Luis M. N. Tavora, Sergio M. M. Faria, Antonio Navarro, Pedro A. A. Assuncao

“…One such tool is the Quaternary Tree and Multi-Type Tree (QTMT) used in the Versatile Video Coding (VVC), which significantly improves coding efficiency over previous standards, but introduces substantially higher computational complexity. To address the challenge of reducing computational complexity with minimal impact on coding efficiency, this paper presents a novel approach for intra-coding 360<inline-formula><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> video in Equirectangular Projection (ERP) format. …”
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Simple variable tap‐length algorithm for high‐noise environment by Ying Wei, Zhibin Yan

“…Only at a slight cost of computational complexity, the proposed algorithm can achieve both small steady‐state fluctuation and fast‐convergence rate of the tap‐length under a high stochastic Gaussian noise condition (signal‐to‐noise ratio = 0 dB) or a deterministic impulsive noise condition.…”
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Channel Estimation Optimization Model in Internet of Things Based on MIMO/OFDM with Deep Extended Kalman Filter by Van Tinh Shi, Dong Ren Nhg

“…However, due to high computational complexity as well as inaccurate channel estimation and remaining weaknesses such as latency and other quality of service criteria, especially Bit Error Rate (BER), Signal Noise Ratio (SNR), and Maximum to Average Power Ratio (PAPR), this research improves these two methods based on the Deep Extended Kalman filter.…”
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Marker and source-marker reprogramming of Most Permissive Boolean networks and ensembles with BoNesis by Paulevé, Loïc

“…In each case, we give an upper bound on their theoretical computational complexity, and give an implementation of the resolution using the BoNesis Python framework. …”
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A multiscale approach to a linear programming problem for calculating a refractive optical element forming a given far-field illumination distribution by D.V. Soshnikov, A.A. Mingazov, L.L. Doskolovich

“…The direct solution of this type of problem presents a huge computational complexity. To overcome this difficulty we use the so-called multiscale approach based on constructing a chain of approximations that are solutions on refining grids.…”
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Review of the matched asymptotic approach of the coupled criterion by Jiménez-Alfaro, Sara, García, Israel García, Doitrand, Aurélien

“…One of its key uses is in Fracture Mechanics, where it provides accurate approximations in the vicinity of the crack tip with low computational complexity. This method can be seamlessly integrated with the Coupled Criterion (CC), which enables the prediction of crack nucleation and propagation in brittle materials. …”
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A REAL TIME FACE RECOGNITION SYSTEM USING ALEXNET DEEP CONVOLUTIONAL NETWORK TRANSFER LEARNING MODEL by LAWRENCE O. OMOTOSHO, IBRAHIM K. OGUNDOYIN, JOSHUA O. OYENIYI, OLUWASHINA A. OYENIRAN

“…The most important issue, regardless of the method used in the face recognition system, is dimensionality and computational complexity, especially when operating on large databases. …”
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EMIKNet: Expanding Multiple-Instance Inverse Kinematics Network for Multiple End-Effector and Multiple Solutions by Youn-Jae Go, Jun Moon

“…Inverse Kinematics (IK) is essential for robot control but suffers from computational complexity as the number of links and end-effectors increases, thereby affecting real-time control accuracy and performance. …”
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Eliminating Network Depth: Genetic Algorithm for Parameter Optimization in CNNs by M. Askari, S. Soleimani, M. H. Shakoor, M. Momeni

“…However, CNNs often require large numbers of parameters, leading to increased computational complexity, prolonged training times, and substantial resource demands. …”
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A lightweight power quality disturbance recognition model based on CNN and Transformer by ZHANG Bide, QIU Jie, LOU Guangxin, ZHOU Can, LUO Qingqing, LI Tianqian

“…A lightweight power quality disturbances (PQDs) recognition model that integrates convolutional neural network (CNN) and Transformer (CaT) is proposed to address the high number of parameters and computational complexity in existing deep learning-based models. …”
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Quantum complexity of time evolution with chaotic Hamiltonians by Vijay Balasubramanian, Matthew DeCross, Arjun Kar, Onkar Parrikar

“…Our analysis relates complexity to familiar properties of physical theories like their spectra and the structure of energy eigenstates and has implications for the hypothesized computational complexity class separations PSPACE BQP/poly and PSPACE BQSUBEXP/subexp, and the “fast-forwarding” of quantum Hamiltonians.…”
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