Hw5 Study guides, Class notes & Summaries

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HW_5 Dynamics HW_5 Dynamics
University of California, Berkeley CS 61C61C HW5
  • University of California, Berkeley CS 61C61C HW5

  • Exam (elaborations) • 6 pages • 2021
  • Q1 Single-Cycle Datapath 4 Points I think we've had enough of Datapath in Lecture and Discussion (or not), but here, have some more anyways! And no, this homework is not optional. We have reprodu ced the RISC-V single-cycle pipeline here. Using the following delays for the rest of the problem. Assume any component not listed is negligible in calculations. ELEMENT REGISTER CLK-TO-Q REGISTER SETUP MUX ALU MEMREAD MEM WRITE REGFILE READ REGFILE Parameter Delay (ps) 30 20 25 200 250 200 150 20 Q1.1...
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Communication Systems - HW5 Notes
  • Communication Systems - HW5 Notes

  • Class notes • 5 pages • 2023
  • Available in package deal
  • ELEC 3400. COMMUNICATION SYSTEMS: Pulse code modulation, line coding, information rate, equalization, amplitude modulation, angle modulation, noise in communication systems.
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HW5_Deferred Annuities and More Complicated Equivalence Calculations_EE HW5_Deferred Annuities and More Complicated Equivalence Calculations_EE
  • HW5_Deferred Annuities and More Complicated Equivalence Calculations_EE

  • Other • 2 pages • 2023
  • Available in package deal
  • A deferred annuity is an annuity that does not begin making payments until a specified date in the future. In engineering economy, deferred annuities are often used to evaluate investments in which cash inflows or outflows are expected to occur at a future date. Engineers use present worth, future worth, annual worth, and nominal rate factors to calculate the value of deferred annuities and compare them to other investment options. In more complicated equivalence calculations, engineers may u...
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STAT 1031 Biostatistics HW5 QUESTIONS WITH VERIFIED ANSWERS
  • STAT 1031 Biostatistics HW5 QUESTIONS WITH VERIFIED ANSWERS

  • Exam (elaborations) • 5 pages • 2021
  • 20 BME 3060: Introduction to Biostatistics Homework #5 Download the data ‘studentdata’ from the package ‘LearnBayes.’ 1. Create a separate column labelled as ‘HoursSlept’ in the ‘studentdata’ folder recording how many hours each student slept the previous night. Obtain summary statistics of all data in the enhanced ‘studentdata.’ 3 points Code: library(LearnBayes) data("studentdata") studentdata$HoursSlept= (studentdata$WakeUp- studentdata$ToSleep) dim(studentdata...
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HW5_SOL ECE 468ECE 468 & 573 Problem Set 5: Dataflow analysis and Loop transformations
  • HW5_SOL ECE 468ECE 468 & 573 Problem Set 5: Dataflow analysis and Loop transformations

  • Exam (elaborations) • 7 pages • 2022
  • ECE 468 & 573 Problem Set 5: Dataflow analysis and Loop transformations Loop transformations For the following problems, consider the code below: 1. X = 2; 2. Y = 10; 3. Y = X * Y; 4. A = Y * X - 2 * Y; 5. B = X / 2 + Y; 6. Z = 10; 7. if (B < Z) goto 12 8. D = Y - Z * Y; 9. Q = Y - 8; 10. Z = Z - Q; 11. goto 7; 12. X = X + A*Y; 13. if (X < Z*100) goto 4; 14. Y = D; 15. halt; 1. Draw the CFG for the code above. Identify the loops in the code. Answer: 1 1. X = 2; 2. Y ...
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block-v1_GTx+ISYE6501x+2T2020a+type@openassessment
  • block-v1_GTx+ISYE6501x+2T2020a+type@openassessment

  • Other • 45 pages • 2021
  • Contents ISYE 6501 HW5 Question 8.1 2 Question 8.2 2 Discussion of the data and disclaimer about my results 2 Start of code for Question 8.2 4 Investigating scaling the data 5 Investigating the unscaled data 15 Looking at regression on unscaled data 23 Evaluation of scaled vs. unscaled data 23 Determining which predictors to use in my regression model using p values 24 Choosing predictors based on Coefficient estimates from scaled data 24 predictions based on different models 2...
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LATEST University of California, Berkeley - CS 70hw5-sol
  • LATEST University of California, Berkeley - CS 70hw5-sol

  • Exam (elaborations) • 9 pages • 2021
  • CS 70 Discrete Mathematics and Probability Theory Fall 2019 Alistair Sinclair and Yun S. Song HW 5 Note: This homework consists of two parts. The first part (questions 1-4) will be graded and will determine your score for this homework. The second part (questions 5-6) will be graded if you submit them, but will not affect your homework score in any way. You are strongly advised to attempt all the questions in the first part. You should attempt the problems in the second part only if you ar...
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block-v1_GTx+ISYE6501x+2T2020a+type@openassessment
  • block-v1_GTx+ISYE6501x+2T2020a+type@openassessment

  • Other • 45 pages • 2021
  • Contents ISYE 6501 HW5 Question 8.1 2 Question 8.2 2 Discussion of the data and disclaimer about my results 2 Start of code for Question 8.2 4 Investigating scaling the data 5 Investigating the unscaled data 15 Looking at regression on unscaled data 23 Evaluation of scaled vs. unscaled data 23 Determining which predictors to use in my regression model using p values 24 Choosing predictors based on Coefficient estimates from scaled data 24 predictions based on different models 2...
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block-v1_GTx+ISYE6501x+2T2020a+type@openassessment
  • block-v1_GTx+ISYE6501x+2T2020a+type@openassessment

  • Other • 45 pages • 2021
  • Contents ISYE 6501 HW5 Question 8.1 2 Question 8.2 2 Discussion of the data and disclaimer about my results 2 Start of code for Question 8.2 4 Investigating scaling the data 5 Investigating the unscaled data 15 Looking at regression on unscaled data 23 Evaluation of scaled vs. unscaled data 23 Determining which predictors to use in my regression model using p values 24 Choosing predictors based on Coefficient estimates from scaled data 24 predictions based on different models 2...
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