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检索条件"任意字段=5th International Conference on Signal Processing and Machine Learning, SPML 2022"

共 777 条记录，以下是41-50 订阅

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Research on 5G signal processing System Based on Computer Intelligent machine learning Algorithm 5

Research on 5G Signal Processing System Based on Computer In...

引用

5th IEEE international conference on Civil Aviation Safety and Information Technology, ICCASIT 2023

作者： Wang, Ruihan Liu, Shu Liu, Jinyu Shandong University of Science and Technology Jinan China

ISBN: (纸本)9798350310603

the data transmission opportunities cannot be fully utilized in 5G multi-user applications due to differences on channel conditions, this project intends to study an improved k-means machine learning method. then the optimal solution method based on the function between angles is proposed to make the selection of Angle parameters simple. the interface is optimized with high performance FPGA, high bandwidth and high sampling rate AD/DA. the test results show that 5Gbps fiber optic data transmission is feasible. the algorithm can intelligently select user devices for scheduling among different user devices of fairness. © 2023 IEEE.

关键词： 5G mobile communication systems

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signal integrity analysis of chip package based on machine learning 5

Signal integrity analysis of chip package based on machine l...

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5th international conference on Mechanical Engineering, Intelligent Manufacturing, and Mechatronics, MEIMM 2024

作者： Wu, Xiaobang Geng, Daoshuang Liu, Yang Huang, Chi Guangxi Key Laboratory of Manufacturing System & Advanced Manufacturing Technology Guilin University of Electronic Technology Guilin541004 China School of Mechanical and Electrical Engineering Guilin University of Electronic Technology Guilin541004 China

ISBN: (数字)9781510686786

ISBN: (纸本)9781510686779

A machine learning approach to chip package signal integrity analysis is proposed. Combining the active learning model and the migrate learning model, the paper improves the performance of the simulation algorithm by fine-tuning the pretraining model, analyzes the convergent speed of the different scale models and the epoch needed before and after the freezing of the different learning rates, it is concluded that the convergence rate is the fastest when the labeled data is 80%, and the period of the unfrozen model is shorter than that of the frozen model. © 2024 SPIE.

关键词： Active learning

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ECG analysis software library based on NLP and ML methods 5

ECG analysis software library based on NLP and ML methods

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5th international conference on Informatics and Data-Driven Medicine (IDDM)

作者： Oliinyk, Yurii Yazenok, Mykhailo Ocheretianyi, Oleksandr Baklan, Igor Lishchuk, Kateryna Beraudo, Elisa Natl Tech Univ Ukraine Igor Sikorsky Kyiv Polytech Inst 37 Prosp Peremohy UA-03056 Kyiv Ukraine

this article discusses the implementation of a software library for the analysis of the electrocardiogram signal. A feature of this library is to improve the functionality and simplify the interaction with existing machine learning software and tools for loading, processing and storing ECG signal datasets by using the Word2Vec model. the library increases development speed of a new software, which involves various ECG analysis. therefore, scientists could more easily implement their ideas related to NLP and ML.

关键词： ECG signal machine learning WFDB software library NLP Word2Vec

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A systematic research of Text-To-Audio generation with diffusion models 5

A systematic research of Text-To-Audio generation with diffu...

引用

5th international conference on signal processing and Computer Science, SPCS 2024

作者： Gao, Yiming Peabody Institute Johns Hopkins University Baltimore21202 United States

ISBN: (数字)9781510686731

ISBN: (纸本)9781510686724

Artificial intelligence is used in people’s daily lives, coping with various kinds of work in almost every aspect of our lives nowadays. Among various kinds of AI, generative AI, ranging from ChatGPT to AI painting, has been discussed most frequently. Some models of generative AI have been used in audio areas, such as denoising or generating audios in recent years. Additionally, though different generative AI has its own advantages, the diffusion model is the most outstanding one among all of those models, leaving people with unforgettable impressions and infinite possibilities by taking advantage of its high fidelity compared to other models, such as GAN. © 2025 SPIE.

关键词： Education and training Autoregressive models Diffusion Data modeling Artificial intelligence Gallium nitride Systems modeling machine learning Design Video

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machine learning Approach on Photoplethysmogram Morphology for Psychiatric Disorders Prediction 5

Machine Learning Approach on Photoplethysmogram Morphology f...

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5th international conference on Communications, signal processing, and their Applications (ICCSPA)

作者： Awang, Azwani Nayan, Nazrul Anuar Jaafar, Nik Ruzyanei Nik Suboh, Mohd Zubir Rahman, Khairul Anuar A. Ismail, Siti Nor Ashikin Univ Kebangsaan Malaysia Dept Elect Elect & Syst Engn Ukm Bangi Malaysia Hosp Canselor Tuanku Muhriz Dept Psychiat Wp Kuala Lumpur Malaysia Univ Tekninal Malaysia Melaka Dept Elect & Comp Engn Technol Malacca Malaysia

ISBN: (纸本)9781665482370

Psychiatric disorders (PDs) interfere with one's functioning and greatly affect a person's quality of life. Prompt diagnosis and intervention at the early stages of these illnesses are important. However, most people are oblivious or unaware of their mental health status as the symptoms may not be easily recognizable. Consequently, complications occur later in life. In this study, a machine learning (ML) approach that distinguishes between case (PD- diagnosed patients) and control (healthy) groups was developed using photoplethysmogram (PPG) morphology. 92 subjects with gender and age- matched PPG data were collected during two phases;baseline and stimulus state of a 10-min experiment. 60 features from PPG morphology were extracted from each phase, and another 30 were obtained from differences between the two phases. A total of 27 out of 90 features exhibited a significant difference. Twelve features extracted by heatmap based on the correlation analysis were fed to five types of ML algorithms: discrimination analysis, k-nearest neighbor, decision tree, support vector machine, and artificial neural network (ANN). the results showed the best performance of 92.86%, 100.00%, and 96.43% for sensitivity, specificity, and accuracy by ANN. thus, a PD prediction model was developed using machine learning techniques from PPG morphology extraction.

关键词： Bio signals Statistical analysis Correlation analysis machine learning

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2022 5th international conference on Communications, signal processing, and their Applications, ICCSPA 2022

2022 5th International Conference on Communications, Signal ...

引用

5th international conference on Communications, signal processing, and their Applications, ICCSPA 2022

ISBN: (纸本)9781665482370

the proceedings contain 67 papers. the topics discussed include: a design of a mmWave compact antenna with a microstrip line balun feed for 5G communications;a machine learning based design of mmWave compact array antenna for 5G communications;an efficient hardware accelerator for lossless data compression;a generic real time autoencoder-based lossy image compression;machine learning-based electric vehicle charging demand prediction using origin-destination data: a UAE case study;a multibeam antenna for multi-orbit LEO satellites and terminals with a very simple tracking technique;the use of capsule endoscopic examination videos in the detection of abnormalities in the gastrointestinal tract;dynamic maps requirements for autonomous navigation on construction sites;and improved Bayesian learning algorithms for recovering block sparse signals with known and unknown borders.

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learning Analytics and machine learning 5

Learning Analytics and Machine Learning

引用

5th international conference on signal processing and Information Security, ICSPIS 2022

作者： Almaazmi, Aisha Karmastaji, Elham Atallah, Shadi Alkhazaleh, Hamzah Ali Manoor, Wathiq University of Dubai College of Engineering and IT Academic City Dubai14143 United Arab Emirates

ISBN: (纸本)9781665492652

this paper integrate the state-of-the-art processes, practices, and challenges of applying learning analytics and data modeling methods in learning and teaching contexts. A large amount of research employed analytics techniques to support the learners and their learning environments to improve learning outcomes and performance. this study aims to analyze learning Analysts in data science, especially how they can be used for better learning processes. this study uses a secondary research design to collect data from various online databases. these databases include Google Scholar and ProQuest. Only research published in 10 years is considered to ensure the recency of the extracted insights and information. the research outcome is presented as a taxonomy for learning analytics and the associated machine learning application in the education domain. © 2022 IEEE.

关键词： Computer aided instruction

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Breast Cancer Detection and Prediction using Federated Multicriteria machine learning 5

Breast Cancer Detection and Prediction using Federated Multi...

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5th international conference on signal processing and Information Security, ICSPIS 2022

作者： Repetto, Marco La Torre, Davide University of Milano-Bicocca Department of Economics Management and Statistics Milan Italy SKEMA Business School Université Côte d'Azur Sophia-Antipolis France University of Milan Department of Oncology Milan Italy

ISBN: (纸本)9781665492652

Breast cancer is still one of the most common cancers in women, and it is also the leading cause of mortality among women. Breast cancer detection has been improved using a variety of machine learning and Deep learning techniques. Federated learning is a distributed learning technique that allows models to be trained on a vast set of decentralized data. In this paper we present a new Multiple Criteria Optimization approach for Federated learning. We use Goal Programming in particular to address the Federated learning problem's diverse set of objectives. Numerical experiments also demonstrate the efficacy of this strategy in terms of performance. © 2022 IEEE.

关键词： Deep learning

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Speech signal Feature Extraction Method of Tibetan Speech Synthesis System Based on machine learning 5th

Speech Signal Feature Extraction Method of Tibetan Speech Sy...

引用

5th EAI international conference on Advanced Hybrid Information processing (ADHIP)

作者： Liu, Ze-guo Northwest Minzu Univ Key Lab Chinas Natl Linguist Informat Technol Lanzhou 730000 Peoples R China

ISBN: (纸本)9783030945510;9783030945503

In order to improve the accuracy of Tibetan speech synthesis, a feature extraction method of Tibetan speech synthesis system based on machine learning is proposed. Based on the analysis of Tibetan speech text content, the construction of speech synthesis system is realized. By judging the level of Tibetan prosody, a synthetic encoder is designed to realize the feature extraction of Tibetan speech signal. According to the experimental results, under the condition of normal speaking speed and identical Tibetan speech content, the Tibetan speech synthesized by the speech signal feature extraction method of Tibetan speech synthesis system based on machine learning is more accurate.

关键词： machine learning Tibetan Synthesis system signal extraction

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Analysis of Diabetes mellitus using machine learning Techniques 5

Analysis of Diabetes mellitus using Machine Learning Techniq...

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5th international conference on Multimedia, signal processing and Communication Technologies (IMPACT)

作者： Bhat, Salliah Shafi Selvam, Venkatesan Ansari, Gufran Ahmad Ansari, Mohd Dilshad BS AbdurRahman Crescent Inst Sci & Technol Chennai 48 Tamil Nadu India MITWPU Fac Sci Pune 411038 Maharashtra India Guru Nanak Univ Dept Comp Sci & Engn Hyderabad India

ISBN: (纸本)9781665476478

Diabetes Mellitus (DM) often known as hyperglycemia is caused by high blood sugar levels. Although DM is a metabolic chronic disease. Treatment and early detection are essential to reducing the risk of serious outcomes. the World Health Organization (WHO) reports that diabetes has a significant mortality rate causing 1.5 million deaths worldwide. the disease can be identified early because to technology tremendous improvements. In order to build a model with a few variables based on the PIMA dataset this research focuses on evaluating diabetes patients as well as diabetes diagnosis using various machine learning Techniques (MLT). Exploratory data analysis is the first step in our process after which the information is transferred for data pre-processing and feature selection. the relevant features are chosen and the data is then training and testing using three different MLT such as Support Vector machine (SVC), Random Forest (RF) and K-Nearest Neighbors (KNN). Amongst all of the classifiers Random Forest has the highest accuracy of 97.75% followed by Support Vector machine (82.25%) and K-Nearest Neighbors (86.25%).

关键词： Diabetes Mellitus Feature Selection machine learning Techniques Support Vector machine Random Forest K-Nearest Neighbors

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