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Decimal to IEEE 754 Floating Point Representation | เรียนรู้การเขียนโปรแกรมออนไลน์ ที่เว็บไซต์ Marketingtangtruong.com

คุณกำลังพยายามหาข้อมูลเกี่ยวกับหัวข้อการหาเงินออนไลน์หรือไม่? คุณกำลังมองหาหัวข้อที่เหมาะสม Decimal to IEEE 754 Floating Point Representation หรือไม่? ถ้าเป็นเช่นนั้นโปรดอ่านบทความนี้ทันที.

Decimal to IEEE 754 Floating Point Representation | การเขียนโปรแกรมการเรียนรู้ด้วยตนเอง ง่ายที่สุด

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รูปภาพที่เกี่ยวข้องกับหัวข้อ floating point.

Decimal to IEEE 754 Floating Point Representation
Decimal to IEEE 754 Floating Point Representation

คุณสามารถดูข้อมูลเพิ่มเติมเกี่ยวกับ คู่มือการเขียนโปรแกรม ง่ายที่สุด ที่นี่: ที่นี่.

ควรอ่านเนื้อหาที่เกี่ยวข้องกับหัวข้อDecimal to IEEE 754 Floating Point Representation.

This video is for ECEN 350 – Computer Architecture at Texas A&M University..

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การค้นหาที่เกี่ยวข้องกับหัวข้อDecimal to IEEE 754 Floating Point Representation.

floating point

Decimal to IEEE 754,Floating Point,IEEE 754

#Decimal #IEEE #Floating #Point #Representation

Gianni Towne

สวัสดีทุกคนฉันชื่อ Gianni Towne ฉันเป็นผู้เชี่ยวชาญด้านการตลาดดิจิทัลเครือข่ายคอมพิวเตอร์การเขียนโปรแกรม เว็บไซต์นี้ฉันสร้างขึ้นโดยมีวัตถุประสงค์เพื่อแบ่งปันความรู้ให้กับทุกคนโดยไม่เสียค่าใช้จ่าย

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33 Comments

  1. I have one question for you. I will appreciate it if you will answer it. 1st q: How did you find out the exponent bias for single precision is 127?

  2. 64-bit notation is basically just extended notation. The exponent has 11 bits instead of 8 (allowing for bigger and smaller numbers with more precision), as well as the mantisa has 52 bits instead of 23 here. This is the double precision format, and essentially can store much larger numbers, and much smaller numbers with finer precision. There is even a decimal format using 32 and 64 bits, that is being used in financial applications for example, due to the nature of binary formats losing some precision when rounding the decimal points. Naturally, computers cannot store infinitely large mantissa, which limits the precision and introduces some quirks that are kind of limiting in certain applications, especially when dealing with decimal values, like money, because they introduce a rounding error into the calculations, and therefore it means that the computer looks at the number and tells you that instead of 0.30 £, the result is 0.3000000000000000000004 £ – yeah, you can say this is close enough, but not for computers – if you try to compare like 0.1 + 0.2 calculation result with 0.3 in certain interpreted languages (JavaScript for example), it says that these values are not equal. And it is kind of frustrating when you are debugging something and eventually after hours of endless debugging you find out that the issue is caused by a stupid rounding error. The decimal format gets rid of that issue. It does actually reduce the efficiency of storing the value, but in the end, it kind of introduces neat decimal precision that is needed. And for decimal points, you do not need much precision in financial market anyway, as most of the time, you'll deal with only two decimal places anyway…

  3. You are Awesome!!! Very clear and concise explanation, and very detailed example.

  4. Very short and Crisp explanation, thanks a lot. I have one question a 32 bit in binary can have only (2^(32) -1 ) combinations. But we can have any count of floating point number, for example 23.5f, 2.78f. 54.8769f etc. Then how can we have a unique 32 bit pattern for each FP number when the combination count is only (2^(32) -1 )?

  5. Amazing explanation! It was very neat easy to follow along with. Super helpful thank you!

  6. The best explanation after after watching many videos. Congratulations

  7. I cant understand why colleges and universities wouldn't find and hire a normal human being like this person in this video to teach students this sort of materials in the class instead of those "Professors" whom I have doubt they became professors illegally.

  8. Thanks alot. Saved me from watching my professors 1 hour lecture:(🧡🧡🧡🧡🧡🧡🧡

  9. wow you sound so young but yet your so smart, I have a lot of respect for you dude keep it up.

  10. Good explanation, but I think there is a mistake in it. The binary should be written with MSB first, and LSB last. The whole part should be concatenated to the fraction by its LSB.

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