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This paper investigates use of a machine learnt model for recognition of individually words spoken in Urdu language. Speech samples from many different speakers were utilized for modeling. Original time-domain samples are normalized and pre-processed by applying discrete Fourier transformation for speech feature extraction. In frequency domain, high degree(More)
This paper presents a framework that utilizes Boolean Difference theory to find test vectors for stuck-at-fault detection. The framework reads in structural-style Verilog models, and automatically injects single stuck-at-faults (either stuck-at-zero or stuck-at-one) into the models. The simulations are then performed to find minimal sets of test vectors.(More)
This research paper describes Multiuser detection with minimized Multiple Access Interference (MAI). Multiuser detection seeks to enhance the performance of non-orthogonal signaling schemes for multiple access communications by combating the MAI caused by the presence of more than one user in the channel. The conventional Code Division Multiple Access(More)
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