15 papers · ranked by Valyu relevance
Julia Lieb, Michael Schaller
The construction of Maximum Distance Profile (MDP) convolutional codes in general requires the use of very large finite fields. In contrast convolutional codes with optimal column distances maximize the column distances for a given arbitrary finite field. In this paper, we present a construction of such convolutional…
Streit, Julian, Weindel, Franziska + 2 more
—We consider the reconstruction of a codeword from multiple noisy copies that are independently corrupted by insertions, deletions, and substitutions. This problem arises, for example, in DNA data storage. A common code construction uses a concatenated coding scheme that combines an outer linear block code with an…
Lu Xu, Xu Chen, Yixin Ma, Rui Shi + 4 more
Due to the critical role of channel coding, convolutional code recognition has attracted growing interest, particularly in non-cooperative communication scenarios such as spectrum surveillance. Deep learning-based approaches have emerged as promising techniques, offering improved classification performance. However…
Yuwei Ma, Yingke Lei, Changming Liu, Wei Wang + 6 more
Facing heterogeneous signals increasing in dynamic spectrum, cognitive radio urgently needs blind channel coding identification. This technology addresses the core challenge of unknown coding schemes in non-cooperative communications. Existing methods are typically restricted to specific coding types and suffer from…
Matteo De Matola, Giorgio Arcara
Convolutional neural networks (CNNs) are a class of artificial neural networks (ANNs). Since the early 2010s, they have been widely adopted as models of primate vision and classifiers of neuroimaging data, becoming relevant for a wealth of neuroscientific fields. However, the majority of neuroscience researchers come…
John Chiang
—Privacy-preserving inference of convolutional neural networks (CNNs) using homomorphic encryption has emerged as a promising approach for enabling secure machine learning in untrusted environments. In our previous work [[1]], we introduced a matrix-encoding strategy that allows convolution and matrix multiplication to…
Dale Zhou, Sharon M. Noh, Nora C. Harhen, Nidhi V. Banavar + 3 more
The ability to discriminate similar visual stimuli has been used as an important index of memory function. This ability is widely thought to be supported by expanding the dimensionality of relevant neural codes, such that neural representations for the similar stimuli are maximally distinct, or “separated.” An…
Kiran Nair, Hubert Cecotti
Non-invasive Brain-Computer Interfaces (BCIs) based on Code-Modulated Visual Evoked Potentials (C-VEPs) require highly robust decoding methods to address temporal variability and session-dependent noise in EEG signals. This study proposes and evaluates several deep learning architectures, including convolutional neural…
Dan Jacobellis, Neeraja J. Yadwadkar
Modern sensors generate rich, high-fidelity data, yet applications operating on wearable or remote sensing devices remain constrained by bandwidth and power budgets. Standardized codecs such as JPEG and MPEG achieve efficient trade-offs between bitrate and perceptual quality but are designed for human perception…
Jirui Fu, Helen J Huang, Yue Wen
Convolutional neural networks (CNNs) have shown promise in decoding neural drive from high-density surface electromyography (HD-sEMG) signals. However, the effects of convolutional kernel dimensionality on the generalizability and computational efficiency of CNN-based neural drive decoding remain unclear. This study…
Authors not listed
Metal–organic frameworks (MOFs) represent a versatile class of porous materials, yet efficiently exploring their vast chemical space for target gas adsorption properties remains a major challenge. MOFid, a text-based encoding of MOF structures, has enabled large-scale data mining using natural language processing (NLP)…
Hiroshi Tamura
Neurons in the cerebral cortex are organized topographically. In the primate visual cortex, neighboring neurons often respond to similar stimulus parameters, such as receptive field position, orientation, color, and spatial frequency. Preferred stimulus parameters change smoothly across the cortical surface. If such…
Kees Schouhamer Immink, Jos H. Weber, Tuan Thanh Nguyen, Kui Cai + 2 more
The design of low-complexity and efficient constrained codes has been a major research item for many years. This paper reports on a versatile method named concatenated constrained codes for designing efficient fixed-length constrained codes with small complexity. A concatenated constrained code comprises two (or more)…
Yuichiro Takeuchi, Yusuke Imoto, Shunya Kato
We conducted a series of experiments to evaluate the performance of Ninja Codes. First, to test the accuracy of region/corner detection and message (code ID) retrieval, i.e., the entire detection pipeline, we prepared 25 high-resolution images of common environmental textures such as wood, marble, asphalt, etc., and…
Authors not listed
Next Generation Risk Assessment (NGRA) promotes animal-free, exposure-informed, and hypothesis-driven approaches to chemical safety assessment. In silico tools, such as quantitative structure-activity relationship (QSAR) models, are valuable new approach methodologies (NAMs) for use in NGRA. However, the practical…