Digital Signal Processing By Venkataramani And Bhaskar Pdf 30
Digital Signal Processing By Venkataramani And Bhaskar Pdf 30
Digital Signal Processing By Venkataramani And Bhaskar Pdf 30
UNIT II DECIMATION
PART 4: Applications of decimation
1. Digital sampling. 2. Decimation factor. 3. Decimation factors. 4. Decimation factor and decimation schemes. 5. Oversampling versus decimation. 6. Decimation versus arbitrary signals. 7. Decimation of periodic signals. 8. Multirate systems. 9. Circuit topologies for multirate signal processing. 10. Interpolation based sampling rate conversion. 11. Lowpass and band-pass filtering. 12. Beam forming. 13. Signal processing by decimation and intersample interpolation. 14. Hardware implementation of over sampling schemes. 15. Oversampling schemes for resolution improvement in case of multiple input multiple output systems.
UNIT III INTERPOLATION: Introduction to interpolation techniques. 2. Interpolation of periodic signals. 3. Interpolation of signals with arbitrary parameters. 4. Interpolation for resolution improvement. 5. Interpolation based sampling rate conversion. 6. Introduction to lowpass and band-pass filtering. 7. Hardware implementation of interpolation schemes. 8. Introduction to Digital Filter Banks. 9. Introduction to sub-band coding.
UNIT IV.FIR DIGITAL FILTER DESIGN: Logician approach, Generation of m bit N-Stage FIR Filter, Finite impulse response filter, Cascading, In-block FIR design by Decimation, Indirect Filter arrangements. Implementations, Programs, Implementation of FIR filters
UNIT V.FIR DIGITAL FILTER DESIGN: Selection of passband and stopband, IIR analogue filters, IIR digital filters, Infinite Impulse Response filters, Reversibility of FIR digital filters, Phase Transitions, Properties of FIR and IIR digital filters. Implementation Examples.
The purpose of this research is to provide a method to reconstruct real-time holographic video images through the recorded analog holographic data. As a matter of fact, the original holographic image is recorded by the intensity interference of the object wave and the reference wave which is called as the hologram. Based on the recorded hologram, the object is reconstructed by either the traditional Holographic Optical Element (HOE) or the Electronic Holographic Optical Element (EHOE). However, the direct HOE/EHOE requires a huge memory storage, power consumption and high data rate since they record the interference intensity. The proposed method reconstructs the real-time holographic video images by exploiting the advantage of the two dimensional (2D) photo-sensor array. The holographic video information is divided into certain frames (for instance, 256 frames for one second video information). After scanning each frame, each single frame is converted into digital 2D data by the 2D photo-sensor array. Then the pixel data is processed to reconstruct the holographic image as a real-time video by the digital back-end process. The experimental results and discussion show that the proposed method can reconstruct the holographic video images, and the reconstructed video is clear and sharp. The proposed method is useful in providing high-quality real-time holographic video images.
Interpolation in the frequency domain has been very efficiently used in magnetic particle imaging (MPI) based on the superparamagnetic properties of ferromagnetic nanoparticles. The frequency-domain interpolation technique has been successfully employed to generate frequency-domain images from magnetic images. However, such images generated from the frequency-domain interpolated magnetic images are found to be less accurate than their direct magnetic counterparts in the time-domain. In this paper, we present a time-domain weighted superposition method for the frequency-domain interpolation. In such a framework, magnetic images of nanoparticles can be directly interpolated using a weighted superposition of the frequency-domain image. Using such an approach, the weighted superposition (WS) method gives us the opportunity to extract a remarkable amount of frequency-domain information from the magnetic signal captured at the detector, resulting in higher quality images of the nanoparticles. In this paper, we show that the application of the WS method in MIPs is highly promising for the development of a real-time, high-resolution, and high-speed MIP system in the MHz frequency domain to further advance the MPI technique.
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