فهرست مقالات Vector Quantization

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  1 - Joint Source and Channel Analysis for Scalable Video Coding Using Vector Quantization over OFDM System
  Farid Jafarian Hassan Farsi
  10.7508/jist.2014.04.008
  Conventional wireless video encoders employ variable-length entropy encoding and predictive coding to achieve high compression ratio but these techniques render the extremely sensitive encoded bit-stream to channel errors. To prevent error propagation, it is necessary t چکیده کامل

  Conventional wireless video encoders employ variable-length entropy encoding and predictive coding to achieve high compression ratio but these techniques render the extremely sensitive encoded bit-stream to channel errors. To prevent error propagation, it is necessary to employ various additional error correction techniques. In contrast, alternative technique, vector quantization (VQ), which doesn’t use variable-length entropy encoding, have the ability to impede such an error through the use of fix-length code-words. In this paper, we address the problem of analysis of joint source and channel for VQ based scalable video coding (VQ-SVC). We introduce intra-mode VQ-SVC and VQ-3D-DCT SVC, which offer similar compression performance to intra-mode H.264 and 3D-DCT respectively, while offering inherent error resilience. In intra-mode VQ-SVC, 2D-DCT and in VQ-3D-DCT SVC, 3D-DCT is applied on video frames to exploit DCT coefficients then VQ is employed to prepare the codebook of DCT coefficients. In this low bitrate video codecs, high level robustness is needed against the wireless channel fluctuations. To achieve such robustness, we propose and calculate optimal codebook of VQ-SVC and optimal channel code rate using joint source and channel coding (JSCC) technique. Next, the analysis is developed for transmission of video using an OFDM system over multipath Rayleigh fading and AWGN channel. Finally, we report the performance of these schemes to minimize end-to-end distortion over the wireless channel. پرونده مقاله
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  2 - Self-Organization Map (SOM) Algorithm for DDoS Attack Detection in Distributed Software Defined Network (D-SDN)
  Mohsen Rafiee Alireza  shirmarz
  10.52547/jist.15644.10.38.120
  The extend of the internet across the world has increased cyber-attacks and threats. One of the most significant threats includes denial-of-service (DoS) which causes the server or network not to be able to serve. This attack can be done by distributed nodes in the netw چکیده کامل

  The extend of the internet across the world has increased cyber-attacks and threats. One of the most significant threats includes denial-of-service (DoS) which causes the server or network not to be able to serve. This attack can be done by distributed nodes in the network as if the nodes collaborated. This attack is called distributed denial-of-service (DDoS). There is offered a novel architecture for the future networks to make them more agile, programmable and flexible. This architecture is called software defined network (SDN) that the main idea is data and control network flows separation. This architecture allows the network administrator to resist DDoS attacks in the centralized controller. The main issue is to detect DDoS flows in the controller. In this paper, the Self-Organizing Map (SOM) method and Learning Vector Quantization (LVQ) are used for DDoS attack detection in SDN with distributed architecture in the control layer. To evaluate the proposed model, we use a labelled data set to prove the proposed model that has improved the DDoS attack flow detection by 99.56%. This research can be used by the researchers working on SDN-based DDoS attack detection improvement. پرونده مقاله