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The final exam questions for the ece-c690: dependable computing course, focusing on error detection and correction techniques. The exam covers topics such as error correction using separable 3-of-6 codes, hamming codes, cyclic codes, time redundancy approaches, and checksums in matrix multiplication. Students are required to answer questions related to hardware designs, parity equations, generating polynomials, ripple-carry adders, and data integrity.
Typology: Exams
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The midterm is due in class Monday, March 16, 2009. Please answer all questions. You are not allowed to collaborate with others.
(a) (10 points) A simple technique for error correction is to pick the nearest code word as the correct word once an error has been detected. Develop a hardware design that performs the error correction for a separable 3-of-6 code by choosing the nearest valid code word. Make the necessary assumptions and state them clearly in your answer. Points will be awarded, in part, based on the efficiency of your design.
(b) (15 points) The following is a parity matrix for a Hamming code:
d 1 c 1 d 2 c 2 d 3 c 3 d 4 0 1 1 1 0 1 0 1 0 0 1 0 1 1 1 1 0 0 1 1 0
where ci is a check bit and di is a data bit.
(c) (10 points) Consider an n-bit code word and show that if the generating polynomial G(X) of a cyclic code has more than one term, all single-bit errors will be detected.
(a) (15 points) Investigate the error detection capability of the following time redundancy approach when used on a ripple-carry adder. During the first addition, the operands are encoded using a 3N arithmetic code. During the second addition, the operands are encoded using a 5N arithmetic code. Will this scheme detect any single error that can occur in the adder, and why? Will this approach detect any double errors that can occur in the adder, and why?
(b) (10 points) Demonstrate the use of checksums in matrix multiplication to detect, locate, and correct an error by multiplying the following two matrices. You must first augment each matrix to include the necessary checksum rows and columns. Show the augmented matrices, the resulting matrix product, and explain how the erroneous value is located and corrected. Assume that element (2, 2) of the matrix product is calculated incorrectly when demonstrating the technique.