Question 2a) Determine the sampling rate for an analog telephone signaltransmitted across a single channel of a T1 line with a datarate of 1.8 Mbps (megabits per second), assuming that asingle sample is converted to a 16-bit integer.b) A digital sound recorder captures sound from the real-world, processes the audio and stores it in binary form.Using the principles of digital signal processing, practicallyexplain how this phenomenon occurs.c) Using the IEEE Standard 754 single precision for floatingpoint numbers, represent the number-1.101110011011 x 223 as a 32 bit floating pointXnumber. Question 1a) A 9-bit binary number is used to represent an analog valuein the range from 120 ounces to 600 ounces, determine theresolution of the system and interprete yourresult.b) Represent each of the following integers as 10-bit two'scomplement binary numbers.i) -18510ii) 15610iii) -20510iv) 16910e) Explain the term duty cycle and determine the pulseduration of a periodic pulse train whose duty cycle is 30%and frequency is 2.5Mhz. Interprete your results.

As here multiple questions are available I am solving first two parts, a & b a)

a) Determine the sampling rate for an analog telephone signal transmitted across a single channel of a T1 line with a data rate of 1.8 Mbps (megabits per second), assuming that a single sample is converted to a 16-bit integer.

a) Determine the sampling rate for an analog telephone signal transmitted across a single channel of a T1 line with a data rate of 1.8 Mbps (megabits per second), assuming that a single sample is converted to a 16-bit integer.

Introductory Circuit Analysis (13th Edition)

13th Edition

ISBN:9780133923605

Author:Robert L. Boylestad

Publisher:Robert L. Boylestad

Chapter1: Introduction

Section: Chapter Questions

Problem 1P: Visit your local library (at school or home) and describe the extent to which it provides literature...

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Concept explainers

Quantization and Resolution

Quantization is a methodology of carrying out signal modulation by the process of mapping input values from an infinitely long set of continuous values to a smaller set of finite values. Quantization forms the basic algorithm for lossy compression algorithms and represents a given analog signal into digital signals. In other words, these algorithms form the base of an analog-to-digital converter. Devices that process the algorithm of quantization are known as a quantizer. These devices aid in rounding off (approximation) the errors of an input function called the quantized value.

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