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Visar resultat 1 - 5 av 13 uppsatser som matchar ovanstående sökkriterier.
1. Analysis of communication protocols used for wireless Sensor networks
Master-uppsats, Linnéuniversitetet/Institutionen för fysik och elektroteknik (IFE)Sammanfattning : Wireless Sensor Networks (WSNs) have attracted growing interest from both realcustomers and the scientific community in the recent years due to their powerfulcapabilities and varied applications. Each wireless sensor node relays data to thebase station (BS) directly in the direct communication protocol. LÄS MER
2. Model-Based versus Data-Driven Control Design for LEACH-based WSN
Master-uppsats, KTH/Maskinkonstruktion (Inst.)Sammanfattning : In relation to the increasing interest in implementing smart cities, deployment of widespread wireless sensor networks (WSNs) has become a current hot topic. Among the application’s greatest challenges, there is still progress to be made concerning energy consumption and quality of service. LÄS MER
3. Speaker Diarization System for Call-center data
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : To answer the question who spoke when, speaker diarization (SD) is a critical step for many speech applications in practice. The task of our project is building a MFCC-vector based speaker diarization system on top of a speaker verification system (SV), which is an existing Call-centers application to check the customer’s identity from a phone call. LÄS MER
4. Hierarchical Clustering of Time Series using Gaussian Mixture Models and Variational Autoencoders
Master-uppsats, Lunds universitet/Matematisk statistikSammanfattning : This thesis proposes a hierarchical clustering algorithm for time series, comprised of a variational autoencoder to compress the series and a Gaussian mixture model to merge them into an appropriate cluster hierarchy. This approach is motivated by the autoencoders good results in dimensionality reduction tasks and by the likelihood framework given by the Gaussian mixture model. LÄS MER
5. Multi-scale clustering in graphs using modularity
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This thesis provides a new hierarchical clustering algorithm for graphs, named Paris, which can be interpreted through the modularity score and its resolution parameter. The algorithm is agglomerative and based on a simple distance between clusters induced by the probability of sampling node pairs. LÄS MER