Transform (FFT). Time Issues Due to the rate-change operators in the filter bank‚ the discrete WT is not time-invariant but actually very sensitive to the alignment of the signal in time. To address the time-varying problem of wavelet transforms‚ Mallat and Zhong proposed a new algorithm for wavelet representation of a signal‚ which is invariant to time shifts.[3] According to this algorithm‚ which is called a TI-DWT‚ only the scale parameter is sampled along the dyadic sequence 2^j (j∈Z) and
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2. WINS SYSTEM ARCHITECTURE 3. WINS NODE ARCHITECTURE 4. WINS MICRO SENSOR 5. WINS MICROSENSOR INTERFACE CIRCUITS 6. ROUTING BETWEEN NODES 7. SHORTEST DISTANCE ALGORITHM 8. WINS DIGITAL SIGNAL PROCESSING 9. PSD COMPARSON 10. WINS MICROPOWER EMBEDDED RADIO 11. HISTORY 12. APPLICATION 13. PROS AND CONS 14. CONCLUSION REFERENCES LIST OF FIGURES
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techniques and the paper also presents the real-time image processing technique used to measure traffic queue parameters. TABLE OF CONTENTS (1) Introduction……………………………………………………… 3 (2) Signal & Image Processing applied to traffic 2.1 Digital Signal 2.2 Need for processing……………………………………… 4 2.3 Parameters measurable…………………………………... 4 2.4 Image analysis system structure…………………………. 4 (3) Stages of image analysis 0 Pipeline preprocessing…………………………………………
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wavefront-array architecture is proposed for the real-time implementation of second-order spatially-bandpass (SBP) 2-D infinite impulse response (IIR) beam filters having potential applications in broadband beamforming of temporally down-converted RF signals. The higher speed of operation and potentially reduced power consumption of the asynchronous architecture of wavefront-array processors (WAPs) in comparison to the conventional synchronous hardware has emerging applications in radio-astronomy‚ radar
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the system. This is don e by designing the input signal‚ which is applied to the system [3]‚ whereas output is taken as impulse response of system. Input signal is used for excitation. In this paper identification has been achieved by basic approaches as variable frequency signa l (chirp)‚ coherence function and pseudo inverse. II. SYSTEM IDENTIFICATION A suitable system is considered for the application at hand. Then a special input signal is designed such that the system captures the behavior
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traditional multi-bit ADC with a sine-wave input signal. This input is sampled at a frequency Fs. According to Nyquist theory‚ Fs must be at least twice the bandwidth of the input signal. When observing the result of an FFT analysis on the digital output‚ we see a single tone and lots of random noise extending from DC to Fs/2 (Figure 1). Known as quantization noise‚ this effect results from the following consideration: the ADC input is a continuous signal with an infinite number of possible states‚ but
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pulse-width modulation (PWM) techniques with a field-programmable gate array (FPGA). Basic PWM and audio playing methods are explained in detail. A sigma-delta modulation module‚ specifically‚ was programmed into a Basys FPGA in Verilog to produce the audio signal. In addition‚ several other Verilog modules were needed to complete the player: a 25 MHz to 44.1 kHz clock converter‚ address counter‚ and byte readers. Documented code for all the modules is provided. The techniques explored here are practical‚ efficient
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spectrum of the DPCM quantization error Power spectral density of the quantization error q measured for intraframe DPCM with a 16 level quantizer π −π 0 0 ωx ωy π −π Bernd Girod: EE398B: Image Communication II DPCM no. 4 Signal distortions due to intraframe DPCM coding Granular noise: random noise in flat areas of the picture Edge busyness: jittery appearance of edges (for video) Slope overload: blur of high-contrast edges‚ Moire patterns in periodic structures. Bernd
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Scheme and Syllabus For M.Tech. Programme In (Information Technology‚ Computer Science & Engineering‚ Information Security) And (Electronics & Communication Engineering‚ Digital Communication‚ Signal Processing‚ RF & Microwave Engineering‚ VLSI Design) Of Regular & Weekend Programme Guru Gobind Singh Indraprastha University Sector – 16 C‚ Dwarka New Delhi – 110 078‚ India www.ipu.ac.in Scheme of Examination for M.Tech.(Regular & weekend) P rogramme has been approved by BoS of USICT
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EEE 310 - OPERATIONAL AMPLIFIERS AND ACTIVE NETWORKS LECTURE NOTES TABLE OF CONTENT 1. INTRODUCTION 2 1.1 Signals 2 1.2 Classification of Signals 4 1.2.1 Digital vs. Analogue 4 1.2.2 Continuous-time vs. Discrete-time 5 1.2.3 Hazy Part of the Classification 5 1.3 System Response 6 1.4 Linearity vs Non-linearity 6 2. AMPLIFIERS 7 2.1 Types of Amplifiers 8 2.1.1 Signal Amplifier 8 2.1.2 Power Amplifier 8 2.2 Amplifier Circuit Symbol 8 2.3 Amplifier Gain 9 2.3.1 Voltage Gain 9 2.3
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