代码搜索：adjustment

找到约 470 项符合「adjustment」的源代码

代码结果 470
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m lms.m

function [h,y] = lms(x,d,delta,N) % LMS Algorithm for Coefficient Adjustment % ---------------------------------------- % [h,y] = lms(x,d,delta,N) % h = estimated FIR filter % y = output array
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www.eeworm.com/read/274133/10887839

h ov2630_hw.h

// // Copyright (c) Microsoft Corporation. All rights reserved. // // // Use of this sample source code is subject to the terms of the Microsoft // license agreement under which you licensed thi
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www.eeworm.com/read/448529/7531898

m lms.m

function [h,y] = lms(x,d,delta,N) % LMS Algorithm for Coefficient Adjustment % ---------------------------------------- % [h,y] = lms(x,d,delta,N) % h = estimated FIR filter % y = output
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www.eeworm.com/read/439437/7709131

m lms.m

function [h,y] = lms(x,d,delta,N) % LMS Algorithm for Coefficient Adjustment % ---------------------------------------- % [h,y] = lms(x,d,delta,N) % h = estimated FIR filter % y = output
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www.eeworm.com/read/438673/7728470

h mapmaker.h

// -*- c++ -*- // Copyright 2008 Isis Innovation Limited // // This header declares the MapMaker class // MapMaker makes and maintains the Map struct // Starting with stereo initialisation from a bun
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www.eeworm.com/read/438673/7728472

h bundle.h

// -*- c++ -*- // Copyright 2008 Isis Innovation Limited #ifndef __BUNDLE_H #define __BUNDLE_H // Bundle.h // // This file declares the Bundle class along with a few helper classes. // Bundle is the
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www.eeworm.com/read/299923/7820421

m lms.m

function [h,y] = lms(x,d,delta,N) % LMS Algorithm for Coefficient Adjustment % ---------------------------------------- % [h,y] = lms(x,d,delta,N) % h = estimated FIR filter % y = output
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www.eeworm.com/read/196830/8055899

m lms.m

function [h,y] = lms(x,d,delta,N) % LMS Algorithm for Coefficient Adjustment % ---------------------------------------- % [h,y] = lms(x,d,delta,N) % h = estimated FIR filter % y = output
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www.eeworm.com/read/196069/8116722

m lms.m

function [h,y] = lms(x,d,delta,N) % LMS Algorithm for Coefficient Adjustment % ---------------------------------------- % [h,y] = lms(x,d,delta,N) % h = estimated FIR filter % y = output
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www.eeworm.com/read/332010/12785148

html sec-adjustmentinternals.html

Adjustment Internals
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