'Matched filter' diaporamas de présentation

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [ The ParthusCeva Ultra Wideband PHY proposal ] Date Submitted: [05 May, 2003] Source: [ Michael Mc Laughlin, Vincent Ashe ] Company [ ParthusCeva Inc. ]

646 views • 60 slides

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [ The ParthusCeva Ultra Wideband PHY proposal ] Date Submitted: [05 May, 2003] Source: [ Michael Mc Laughlin, Vincent Ashe ] Company [ ParthusCeva Inc. ]

633 views • 59 slides

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [The ParthusCeva Ultra Wideband PHY proposal ] Date Submitted: [05 May, 2003] Source: [ Michael Mc Laughlin, Vincent Ashe ] Company [ ParthusCeva Inc. ]

671 views • 58 slides

Unit IV BASEBAND Receiver

1.06k views • 47 slides

Digital Communications

Digital Communications. Chapeter 3. Baseband Demodulation/Detection Signal Processing Lab. Block Diagram of a DCS. Demodulation and Detection. Modeling the received signal. Major Sources of Errors. Inter-Symbol Interference (ISI)

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Chapter 2

Chapter 2. Introduction to spread-spectrum communications Part II. As discussed in Chapter 1 Part I, a spread spectrum modulation produces a transmitted spectrum much wider than the minimum bandwidth required. There are many ways to generate spread spectrum signals.

582 views • 39 slides

Baseband Receiver

Baseband Receiver. Receiver Design: Demodulation Matched Filter Correlator Receiver Detection Max. Likelihood Detector Probability of Error. Transmit and Receive Formatting. Sources of Error in received Signal. Major sources of errors: Thermal noise (AWGN)

1.81k views • 39 slides

RICE experience/ANITA implications

RICE experience/ANITA implications. Review of RICE progress, to date Current Status Focus on major systematic errors and status of understanding of background Possible future improvements and prospectus. Scorecard (in hindsight). (-) electron testbeam run (kudos to David & Peter)

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Status report

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Chapter 21

Chapter 21. R(x) Algorithm. a) Anomaly Detection b) Matched Filter. Definition of terms: A pixel can be represented by. (1). sub image containing N pixels designated by. (2). The target can be specified as an additive signal with a spatial shape characterized by:. (3).

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Digital Communications I: Modulation and Coding Course

Spring - 2013 Jeffrey N. Denenberg Lecture 3b: Detection and Signal Spaces. Digital Communications I: Modulation and Coding Course. Last time we talked about:. Receiver structure Impact of AWGN and ISI on the transmitted signal Optimum filter to maximize SNR

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Communications II

Communications II. Prof. Dr.-Ing. Karl-Dirk Kammeyer Department of Communications Engineering. 4. Optimal Receiver for AGN Optimal AWGN Receiver Generalization for coloured noise Symbol / Bit Error Probability 5. Equalization Linear Equalization Decision Feedback Adaptive Equalization

368 views • 23 slides

Multiplicative Mismatched Filters for Barker Codes

Multiplicative Mismatched Filters for Barker Codes. Adly T. Fam, Indranil Sarkar Department of Electrical Engineering The State University of New York at Buffalo. Outline of presentation. Introduction to Barker codes and compound Barker codes.

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Chapter 20

Chapter 20. Matched Filter Comparison. Targets in a Structured Background. The geometric interpretations of an dimensional data set suggests that the image space can be spanned by a set of p bases vectors according to. (1). When we use the subspace approach we can express the

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Linear Time-Invariant Systems (LTI) Superposition Convolution

Linear Time-Invariant Systems (LTI) Superposition Convolution. Linear Time-Invariant Systems (LTI) Superposition Convolution Causal System. Linear Time-Invariant Systems (LTI) Superposition Convolution Causal System. Causal. Linear Time-Invariant Systems (LTI) Superposition

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FACE DETECTION USING HSV COLOR SEGMENTATION AND MATCHED FILTERING

FACE DETECTION USING HSV COLOR SEGMENTATION AND MATCHED FILTERING. EE 368 DIGITAL IMAGE PROCESSING FINAL PROJECT PRESENTATION 30 MAY 2002 GROUP MEMBERS: Vey Sern Ling Scott Payne. INTRODUCTION. OVERVIEW Project Goals System Block Diagram FACE DETECTION SUB-ROUTINES

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Recovering Burst Injections in LIGO S5 Data

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Progress on Graychip filters

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190 views • 9 slides

Gain (dB)

Automatic Gain Control Response Delay and Acquisition in Direct-Sequence Packet Communications Stephanie Gramc, Clemson University Advisor: Dr. Noneaker. 8. 6. 4. 2. 0. -2. 0. 2. 4. 6. 8. 10. 12. 14. s(t) Preamble Sequence. a 0. a 3. a M-1. 1. 0. a 1. a 2. -1. 0. 1. 2. 3.

150 views • 1 slides