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The University of Akron - ACCOUNTING - 659
Chapter 1MANAGERIALACCOUNTING AND THEBUSINESS ENVIRONMENTPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies, Inc. All rig
The University of Akron - ACCOUNTING - 659
Chapter 2MANAGERIALACCOUNTINGAND COST CONCEPTSPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies, Inc. All rights reserve
The University of Akron - ACCOUNTING - 659
Chapter 3COST BEHAVIOR:ANALYSIS AND USEPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies, Inc. All rights reserved.3-2T
The University of Akron - ACCOUNTING - 659
Chapter 4COST-VOLUME-PROFITRELATIONSHIPSPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies, Inc. All rights reserved.4-2
The University of Akron - ACCOUNTING - 659
Chapter 5SYSTEMS DESIGN:JOB-ORDER COSTINGPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies, Inc. All rights reserved.5-2
The University of Akron - ACCOUNTING - 659
Chapter 6VARIABLE COSTING:A TOOL FORMANAGEMENTPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies, Inc. All rights reserve
The University of Akron - ACCOUNTING - 659
Chapter 7ACTIVITY-BASED COSTING:A TOOL TO AID DECISIONMAKINGPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies, Inc. All
The University of Akron - ACCOUNTING - 659
Chapter 8PROFIT PLANNINGPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies, Inc. All rights reserved.8- 2The Basic Framew
The University of Akron - ACCOUNTING - 659
Chapter 9FLEXIBLE BUDGETS ANDPERFORMANCE ANALYSISPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies, Inc. All rights reser
The University of Akron - ACCOUNTING - 659
Chapter 10STANDARD COSTS ANDOPERATING PERFORMANCEMEASURESPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies, Inc. All rig
The University of Akron - ACCOUNTING - 659
Chapter 11SEGMENT REPORTING,DECENTRALIZATION, AND THEBALANCED SCORECARDPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies
The University of Akron - ACCOUNTING - 659
Chapter 12RELEVANT COSTS FORDECISION MAKINGPowerPoint Authors:Susan Coomer Galbreath, Ph.D., CPACharles W. Caldwell, D.B.A., CMAJon A. Booker, Ph.D., CPA, CIAMcGraw-Hill/IrwinCopyright 2011 by the McGraw-Hill Companies, Inc. All rights reserved.1
Michigan - EECS - 555
$'EECS 555: Digital Communications TheoryWinter 2009Instructor: Prof. Wayne StarkCourse Time: Tuesday and Thursday: 10:40-12:00Ofce Hours: Monday and Wednesday: 11:00-12:00 or by appointment.Ofce: 4242 EECSCourse Notes: Available on lineE-mail: s
Michigan - EECS - 555
$'Lecture Notes 2: Detection TheoryGoals: Optimum Detection in AWGN Optimum Detection with Nusiance (Unwanted) Parameters&%II-1$'M -ary Detection ProblemConsider the problem of deciding which of M hypothesis is true based onobserving a random
Michigan - EECS - 555
$'Error Probability for M signalsGoals1. Exact analysis of M -ary orthogonal signals in AWGN channels.2. Gallager bound for arbitrary signals, arbitrary channel.3. Random Coding Bound.&%III-1$'Error ProbabilityProblem: Determine the error pro
Michigan - EECS - 555
'$Lecture Notes 4: Asymptotic PerformanceIn this lecture we discuss the asymptotic performance of signals. First weconsider the case of M signals in N dimension when transmitted over theadditive white Gaussian noise channel. We let M and N become lar
Michigan - EECS - 555
$'Lecture Notes 5: Noncoherent ReceiversGoals Derive optimum receiver for arbitrary signals in Gaussian noise with arandom phase. Determine performance of two signals in white Gaussian noise. Determine performance of M -orthogonal signals in white
Michigan - EECS - 555
'$Lecture Notes 6: Basic Modulation SchemesIn this lecture we examine a number of different simple modulation schemes.We examine the implementation of the optimum receiver, the error probabilityand the bandwidth occupancy. We would like the simplest
Michigan - EECS - 555
$'Lecture 7Goals Be able to encode using a linear block code Be able to decode a linear block code received over a binary symmetricchannel or an additive white Gaussian channel Be able to decode a turbo product code for an additive white Gaussianc
Michigan - EECS - 555
$'Lecture Notes 8: Trellis CodesIn this lecture we discuss construction of signals via a trellis. That is, signalsare constructed by labeling the branches of an innite trellis with signals froma small set. Because the trellis is of innite length this
Michigan - EECS - 555
'$In this lecture we examine optimum demodulation when the transmitted signalis ltered by the channel and there is additive white Gaussian noise. Theoptimum demodulator chooses the possible transmitted vector that wouldresult in the received vector (
Michigan - EECS - 555
'$Lecture Notes 10: Fading Channels ModelsIn this lecture we examine models of fading channels and the performance ofcoding and modulation for fading channels. Fading occurs due to multiplepaths between the transmitter and receiver. For example, two
Michigan - EECS - 555
'Lecture Notes 11:Direct-Sequence Spread-Spectrum Modulation$In this lecture we consider direct-sequence spread-spectrum systems. Unlikefrequency-hopping, a direct-sequence signal occupies the entire bandwidthcontinuously. The signal is obtained by
Michigan - EECS - 555
EECS 555: Digital Communication TheoryWayne E. StarkCopyright c Wayne E. Stark, 20070-2Contents1Introduction1-11.Communication System Coat of Arms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-22Optimum Receiver Principles1
Michigan - EECS - 555
EECS 452Digital Signal Processing LabLecture 8 Yet More VHDL Start on signals reviewHandouts: Lecture notes1BureaucracyHomework/labs/handouts/officehours Lab 3 posted last night. Removed some stuff from the original Added some stuff Tried to
Michigan - EECS - 555
EECS 452Digital Signal Processing LabLecture 9 DFT ADC/DAC basicsHandouts: Lecture notesThe DFT part of the lecture comes fromUnderstanding Digital Signal Processingby Richard Lyons.Many figures in this presentation are from thesame book as abo
Michigan - EECS - 555
EECS 452Digital Signal Processing LabLecture 12 Course Surveys, Course Overview,Project stuff Finite Impulse Response Filters2/4/091Course Surveys Some things largelyconsistent Learning a lot in lab Lab takes more timethan homework Some not
Michigan - EECS - 555
EECS 452Digital Signal Processing LabLecture 12 HW5 Finite Impulse Response Filters2/4/091Homework 5 Homework 5 will due on Wednesday the 11th. Project proposal One per project group Coverage Define the project goal What needs to be done to a
Michigan - EECS - 555
EECS 452Digital Signal Processing LabLecture 14 More FIR filters Start on IIR2/9/091Admin:Lab 5 Lab 5 split in half Partly because too long Partly because I need to cover some more stuff Effects Lab 6 will be the week after break It is relat
Michigan - EECS - 555
EECS 452Digital Signal Processing LabLecture 15 More FIR filters Start on IIR2/11/09Last time: Due to fire, we fled Pick up from there.Internal overflow It is possible for an internal addition to beoutside of the range -1 to 1 even if outputi
Michigan - EECS - 555
EECS 452Digital Signal Processing LabLecture 16 IIR filter basics Overflow range of terms? Biquads2/13/091Group meetings and presentations Anyone else willing to volunteer to go thisWednesday? Need to meet with C2T2Z today if possible Weekend
Michigan - EECS - 555
EECS 452Digital Signal Processing LabLecture 17 Designing a low pass IIR filter the 452 way And why we do it.2/16/09Todays lecture Is a bit different My major goal is to provide intuition aboutfilter design. lowpass biquad IIR filters specifical
Michigan - EECS - 216
1Automatic ControlThe purpose of this handout is to give you a avor of the subject. If you like whatyou see, take EECS 460!Fig. 1. Basic closed-loop control system.Objective: Adjust the input to a system in order to make the output have desirablepro
Michigan - EECS - 216
110.500.500.50.5110240
Michigan - EECS - 216
Control Systems For ReducedEmissions and Walking RobotsSupplement for Signals and SystemsProfessor J.W. GrizzleAutomotive Basics Fuel + Air ObjectivesPower + Emissions Minimize emissions Minimize fuel consumption Main emissions CO2 and H2O NOx
Michigan - EECS - 216
+RZ WR &RPSXWH D &RQYROXWLRQ ,QWHJUDO1P(t-tO )0tO tO +ttOt = mathematical idealization of a narrow pulse with unit area)LJ ,PSXOVH/HWV )LUVW 5HFDOO :K\ WKH ,PSXOVH 5HVSRQVH LV ,PSRUWDQW" \ W7 >[ W@ /7 , KW5b [~ KW\ W7 >p W@b ~ G~7KH LP
Michigan - EECS - 216
1Energy and Power SignalsJ.W. GrizzleLet x(t) be a signal dened on (, ).Def:x is an energy signal ifx2 (t)dt < , and when this integral isnite, it is dened to be the total energy, E , of the signal.Examples:(a) x(t) = e|t| .x2 (t)dt < =e2|t| dt
Michigan - EECS - 216
1How to Compute Some of the Nonstandard,Extended, or Generalized Fourier TransformsRecall: F-transform exists as a normal function if(a) x(t) is piecewise continuous(b) |x(t)|dt< (absolute integrability)We will look at a few cases where the absolu
Michigan - EECS - 216
Frequency Response Functionsand Transfer FunctionsProfessor J. W. GrizzleEECS DepartmentSummary of What You Have to Know Definition of the Frequency Response FunctionH ( j ) =e j h( )d Response of an LTI system to a phasor, ejty (t ) = e jt H ( j
Michigan - EECS - 216
1Impulse Response of a LTI SystemJ.W. GrizzleLet y (t) = T [x, t] be a LTI system.Def: The impulse response of y (t) = T [x, t] is h(t) := T [, t]Very Important Fact (Theorem) Under certain technical conditions [thatessentially mean, whenever the im
Michigan - EECS - 216
1Introduction to the Fourier TransformContents: Brief summary of key results so far How to go from Fourier series to theFourier Transform2Summary of Where We Are So Far(Signals & Systems):System mapping inputs to outputs, y (t) = T [x, t], may be
Michigan - EECS - 216
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Michigan - EECS - 216
EECS 216Signals and SystemsSupplement for Lecture OneProfessor J.W. Grizzle(Section 2)Course Comments Attendance of lecture is expected;discussion sections are optional, but highlyrecommended. Syllabus and much more are posted on theclass web si
Michigan - EECS - 216
1Spectra of Fourier SeriesConsider x(t) = ck ejkw0 t . The SPECTRUM of x(t) is a plot of |ck | and ckk=versus either k or w = kw0 . Often one just plots the magnitude.Example: x(t) = square wave,ck = k evenk odd02j k10.80.60.40.200.20.4
Michigan - EECS - 216
1Spectra of a Sqaure WaveConsider a signal written as an exponential Fourier series: x(t) = ck ejkw0 t .k=The SPECTRUM of x(t) is a plot of |ck | and ck versus either k or w = kw0 . This isillustrated here for a square wave.32x(t)10123012
Michigan - EECS - 216
1System Analysis with Fourier Series (&$ #!'% " Fig. 1. LTI BIBO stable system.x(t) = jkw0 tk = ck ec0 +k =1 2|ck | cos(kw0 t+ k ), where k = ckHow to compute y (t)? Let H (jw) be the frequency response function. We know thatck ejkw0 t ck
Michigan - EECS - 216
216F07-Sec001: Lecture 29/6/07ToDo Today Logistics O ffic e h o u r s E xam 2 You are here This is where we are goingOffice hours Strategy: Homework is due at thebeginning of class on TuesdaysMTWTh1 1 -1 2 P M (A J )3 :3 0 - 4 :3 0 P M ( J
Michigan - EECS - 216
Five Steps to Graphical Convolution anda Couple of Ways to Turn Old Results into NewG. WakeeldEECS 216 Fall 2007September 20, 2007As promised, please consider the following as you read the material in the book andwork through the homework problems.
Michigan - EECS - 216
EECS 216: Signals and SystemsL[f ]+L1[F ]+ab+pz+ode+ic+roc+pfeG. Wakeeld1Facts1. L[f ] : causal (e.g., strictly zero for t < 0) signals only.2. LB [f ]: causal, anticausal (e.g., strictly zero for t 0, or noncausal signals.3. ROC is required for co
Michigan - EECS - 216
FRF, ODE, and Complex ExponentialsG. Wakeeldfor EECS 216F071The Frequency Response FunctionIn class on September 25, we re-visited what the output of a linear, time-invariant (LTI)system H is when the input is a complex exponential. Setting the inte