M Tech Dissertations

Permanent URI for this collectionhttp://drsr.daiict.ac.in/handle/123456789/3

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Author: search.filters.author.Patel, Chirag R.End date: 2023

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    All-digital delay-line based ultra wide band transmitter architecture in 0.18m CMOS
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2014) Patel, Chirag R.; Mishra, Biswajit
    Ultra-Wide Band (UWB) technology has recently become a viable option for commercial wireless applications that require high data-rate and ultra low power demand. UWB technology operates between the frequency range of 3.1 GHz to 10.6 GHz and has to comply with Federal Communications Commission (FCC) standards with Power Spectral Density (PSD) below -41.3 dBm, that is also the lowest among all existing wireless systems. Thus it has a low communication range with high spatial resolution. Therefore, it finds applications in imaging and high precision positioning systems other than wireless sensor systems. Typically the UWB transmitters are implemented either using Orthogonal Frequency Division Multiplexing (OFDM) or base band techniques. Of all, the all digital technique finds interest within the research community due to the energy efficiency and benefits associated with current and future CMOS scaling. The proposed thesis discusses an all-digital UWB transmitter architecture based on all digital technique. It employs a delay line based architecture that works with Pulse Positioning Modulation (PPM), On Off Keying (OOK) and Delay Based Binary Phase Shift Keying (DB-BPSK) modulation schemes at two variable center frequencies (3.75GHz and 4.25GHz) with a fixed 500MHz bandwidth. The design also satisfies FCC indoor power spectral density requirements. We compare proposed design with the state of the art and conclude that it is comparable to existing designs and in certain cases better in view of the CMOS technology being used. The proposed design is implemented in 0.18mm technology based on a custom digital design employs OOK, PPM and DBBPSK Modulation Schemes. The Pulse Repetition Frequency (PRF) can be 100M, with 2 center frequencies (3.75GHz and 4.25GHz) with output amplitude of 120mV and achieves Energy/pulse at 16.59 pJ/p.
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    Person identification from their hum with inter-session variability compensation
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2012) Patel, Chirag R.; Patil, Hemant A.
    In this thesis, design of person recognition system from their hum is discussed. The emphasis is given to the inter-session variability of the recognition system. Standard database is not available for the inter-session variability of humming-based person recognition systems. Therefore, humming database of 50 subjects is collected in two training and six testing sessions. The MFCC (Mel Frequency Cepstral Coefficients) is the state-of-the-art feature set in the field of speech and speaker recognition systems. In this thesis, another cepstral feature viz., VTMFCC (Variable length Teager energy based MFCC) is used along with MFCC. VTMFCC captures the vocal source information. Two modulation-based features, viz., AM-FM and Q-features are introduced in this thesis. The performance of all of the four features in multi-session environment is evaluated using discriminately-trained polynomial classifier. Polynomial classifier uses out-of-class information while creating person- specific person model. Inter-session variability degrades the performance of person recognition systems due to difference in training and test sessions. This variability can be classified as intrinsic variability and extrinsic variability according to its source of origin. Inter-session variability due to speaker’s health, aging, emotional state, etc. is called intrinsic inter-session variability. The session variability due to environment conditions, noise, change in microphone and acoustic channel is called extrinsic inter-session variability. The inter-session variability degrades the performance of all four features, i.e., MFCC, VTMFCC, AM-FM and Qfeature. The difference in % EER (Equal Error Rate) of particular test session to base test session is used as the inter-session variability measure. The base test session is a test session which is collected with the training session. In this thesis, two new approaches have been proposed for the compensation of inter-session variability, viz., feature-level fusion and model-level fusion. These two approaches reduce the degradation in the performance of person recognition system due to inter-session variability and make the system robust.