On-chip principal component analysis with a mean pre-estimation method for spike sorting

Chen, Tung-Chien; Chen, Kuan-Fu; Liu, Wentai; Chen, Liang-Gee

doi:10.1109/iscas.2009.5118461

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…Their popularity [1,[3][4][5]8,11,[13][14][15]19,[22][23][24] is due to many reasons like low cost hardware implementation, low memory requirement, less processing time and less computational complexity.…”

Section: Introductionmentioning

confidence: 99%

“…The fixed-point algorithm of PCA is also known as fast PCA (FPCA) algorithm. The FPCA algorithm has been recently extended and applied in face recognition [8,14,15], communication [13,24], VLSI architecture design [3][4][5] and in other areas or applications like in Yang et al [23]; Shi and Guo [19]; Lai and Huang [11]; Wang et al [22]; Albanese et al [1]. The feature selection method plays a significant role in identifying crucial genes related to human cancers.…”

Section: Introductionmentioning

confidence: 99%

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A feature selection method using fixed-point algorithm for DNA microarray gene expression data

Sharma

Paliwal²,

Imoto

et al. 2014

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As the performance of hardware is limited, the focus has been to develop objective, optimized and computationally efficient algorithms for a given task. To this extent, fixed-point and approximate algorithms have been developed and successfully applied in many areas of research. In this paper we propose a feature selection method based on fixed-point algorithm and show its application in the field of human cancer classification using DNA microarray gene expression data. In the fixed-point algorithm, we utilize between-class scatter matrix to compute the leading eigenvector. This eigenvector has been used to select genes. In the computation of the eigenvector, the eigenvalue decomposition of the scatter matrix is not required which significantly reduces its computational complexity and memory requirement.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A feature selection method using fixed-point algorithm for DNA microarray gene expression data

Sharma

Paliwal²,

Imoto

et al. 2014

KES

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“…While the PCA method is considered the benchmark spike sorting process, it is computationally expensive and requires a usermanaged training phase for each channel (Chen et al, 2009). This includes redefining the cluster boundaries for each recording session.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic-based spike sorting system

Balasubramanian

Obeid

2011

Journal of Neuroscience Methods

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A hardware implementation of PCA based-on the Networks-on-Chip paradigm

Karnthak

Kumhom

2012

2012 International Symposium on Communications and Information Technologies (ISCIT)

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Principal Component Analysis (PCA) is a significant algorithm that has been applied in various applications. The computations of this algorithm are based on the matrix manipulation including addition, subtraction, and multiplication. This paper proposed a hardware implementation for PCA by using the Networks-on-Chip (NoC) concept as the design paradigm. In the proposed procedure a 2D mesh topology is selected first while PCA algorithm is represented in form of a task graph, which can be divided into 2 levels. In the higher level, tasks are matrix-based algorithms, such as mean computation, which in turn will be mapped onto the NoC topology. Since the NoC is scalable, an appropriate size of 2D mesh will be selected so that the timing of each task in the task chain is matched resulting in an effective pipeline in the higher level. The simulation using SystemC with NoC modeled as Cycle-Accurate showed that an average throughput of 2.20 Gbps and latency of 0.025 cycle/flit were achieved while computing the matrix multiplication of size 112x92 with 81 Processing Element (PE) organize as 9x9 while running with clock speed of 100 MHz.

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On-chip principal component analysis with a mean pre-estimation method for spike sorting

Cited by 4 publications

References 12 publications

A feature selection method using fixed-point algorithm for DNA microarray gene expression data

A feature selection method using fixed-point algorithm for DNA microarray gene expression data

Fuzzy logic-based spike sorting system

A hardware implementation of PCA based-on the Networks-on-Chip paradigm

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