Khalid Sayood - Academia.edu (original) (raw)
Papers by Khalid Sayood
16TH FLOOR ST LOUIS, MO 63102 (US) The present invention provides a new algorithm for assem bling... more 16TH FLOOR ST LOUIS, MO 63102 (US) The present invention provides a new algorithm for assem bling fragments from a long DNA sequence. The algorithm of the invention Solves simultaneously fragment assembly (21) Appl. No.: 10/295,030 related problems. Such as the fragment orientation, overlap and layout phases. This is achieved by clustering fragments with respect to their Average Mutual Information (AMI) (22) Filed: Nov. 13, 2002 profiles using the k-means algorithm. The maximum spanning tree to be used in the multiple alignment
Data Compression Conference, 1994
An edge preserving image coding scheme which can be operated in both a lossy and a lossless manne... more An edge preserving image coding scheme which can be operated in both a lossy and a lossless manner was developed. The technique is an extension of the lossless encoding algorithm developed for the Mars observer spectral data. It can also be viewed as a modification of the DPCM algorithm. A packet video simulator was also developed from an existing modified packet network simulator. The coding scheme for this system is a modification of the mixture block coding (MBC) scheme described in the last report. Coding algorithms for packet video were also investigated.
Typescript (photocopy).Quantization plays an important role in most communication schemes, yet, t... more Typescript (photocopy).Quantization plays an important role in most communication schemes, yet, though extensive results are available for scalar quantization, till recent years very little appeared in the literature concerning the design of vector quantizers. This work presents the first algorithm for designing uniform vector quantizers for various blocklengths (dimensions), which does not utilize a training sequence. The algorithm is motivated by a separation technique which has appeared in the literature and uses least dense covering lattices to generate the quantizers. The algorithm is used to generate quantizers for blocklength up to nine. These are compared with the best available quantizers in the literature and found to compare favorably. The quantizers are used to transform code an image. The results show the improvement to be obtained over scalar quantization. Coding strategies are also presented for both small and large codebooks
it. The source coder output contains redundancy. Source coders and channel coders are generally d... more it. The source coder output contains redundancy. Source coders and channel coders are generally designed separately without reference to each other. This approach is justified by a famous result of Shannons. However, there are many situations in practice in which the assumptions upon which this result is based are violated. Specifically, we ezamine *he situation where there is residual redundancy at the source coder output. We have previously shown that this residual redundancy can be used to provide error correction using a Viterbi decoder. In this paper we present the second half of the design; the design of encoders for this situation. We show through simulation resulfs fhaf *he proposed coders consistently outperform convenfional source-channel coder pairs with gains of up to ledB at high probability of error.
Synthesis Lectures on Biomedical Engineering, 2022
Synthesis Lectures on Signal Processing, 2021
Synthesis Lectures on Signal Processing, 2021
Synthesis Lectures on Signal Processing, 2021
Synthesis Lectures on Signal Processing, 2021
Computational Genomic Signatures
Introduction to Data Compression, 2018
In this chapter, we introduce an increasingly popular method of generating variable-length codes ... more In this chapter, we introduce an increasingly popular method of generating variable-length codes called arithmetic coding. Arithmetic coding is especially useful when dealing with sources with small alphabets, such as binary sources, and alphabets with highly skewed probabilities. It is also a very useful approach when, for various reasons, the modeling and coding aspects of lossless compression are to be kept separate. In this chapter, we look at the basic ideas behind arithmetic coding, study some of the properties of arithmetic codes, and describe an implementation.
16TH FLOOR ST LOUIS, MO 63102 (US) The present invention provides a new algorithm for assem bling... more 16TH FLOOR ST LOUIS, MO 63102 (US) The present invention provides a new algorithm for assem bling fragments from a long DNA sequence. The algorithm of the invention Solves simultaneously fragment assembly (21) Appl. No.: 10/295,030 related problems. Such as the fragment orientation, overlap and layout phases. This is achieved by clustering fragments with respect to their Average Mutual Information (AMI) (22) Filed: Nov. 13, 2002 profiles using the k-means algorithm. The maximum spanning tree to be used in the multiple alignment
Data Compression Conference, 1994
An edge preserving image coding scheme which can be operated in both a lossy and a lossless manne... more An edge preserving image coding scheme which can be operated in both a lossy and a lossless manner was developed. The technique is an extension of the lossless encoding algorithm developed for the Mars observer spectral data. It can also be viewed as a modification of the DPCM algorithm. A packet video simulator was also developed from an existing modified packet network simulator. The coding scheme for this system is a modification of the mixture block coding (MBC) scheme described in the last report. Coding algorithms for packet video were also investigated.
Typescript (photocopy).Quantization plays an important role in most communication schemes, yet, t... more Typescript (photocopy).Quantization plays an important role in most communication schemes, yet, though extensive results are available for scalar quantization, till recent years very little appeared in the literature concerning the design of vector quantizers. This work presents the first algorithm for designing uniform vector quantizers for various blocklengths (dimensions), which does not utilize a training sequence. The algorithm is motivated by a separation technique which has appeared in the literature and uses least dense covering lattices to generate the quantizers. The algorithm is used to generate quantizers for blocklength up to nine. These are compared with the best available quantizers in the literature and found to compare favorably. The quantizers are used to transform code an image. The results show the improvement to be obtained over scalar quantization. Coding strategies are also presented for both small and large codebooks
it. The source coder output contains redundancy. Source coders and channel coders are generally d... more it. The source coder output contains redundancy. Source coders and channel coders are generally designed separately without reference to each other. This approach is justified by a famous result of Shannons. However, there are many situations in practice in which the assumptions upon which this result is based are violated. Specifically, we ezamine *he situation where there is residual redundancy at the source coder output. We have previously shown that this residual redundancy can be used to provide error correction using a Viterbi decoder. In this paper we present the second half of the design; the design of encoders for this situation. We show through simulation resulfs fhaf *he proposed coders consistently outperform convenfional source-channel coder pairs with gains of up to ledB at high probability of error.
Synthesis Lectures on Biomedical Engineering, 2022
Synthesis Lectures on Signal Processing, 2021
Synthesis Lectures on Signal Processing, 2021
Synthesis Lectures on Signal Processing, 2021
Synthesis Lectures on Signal Processing, 2021
Computational Genomic Signatures
Introduction to Data Compression, 2018
In this chapter, we introduce an increasingly popular method of generating variable-length codes ... more In this chapter, we introduce an increasingly popular method of generating variable-length codes called arithmetic coding. Arithmetic coding is especially useful when dealing with sources with small alphabets, such as binary sources, and alphabets with highly skewed probabilities. It is also a very useful approach when, for various reasons, the modeling and coding aspects of lossless compression are to be kept separate. In this chapter, we look at the basic ideas behind arithmetic coding, study some of the properties of arithmetic codes, and describe an implementation.