3 citations · 6 across the 7 of their papers we have counts for
8 papers
Block Walsh-Hadamard Transform Based Binary Layers in Deep Neural Networks
Hongyi Pan, Diaa Badawi, Ahmet Enis Cetin
Convolution has been the core operation of modern deep neural networks. It is well-known that convolutions can be implemented in the Fourier Transform domain. In this paper, we pro…
Detecting Anomaly in Chemical Sensors via L1-Kernels based Principal Component Analysis
Hongyi Pan, Diaa Badawi, Ishaan Bassi +2
We propose a kernel-PCA based method to detect anomaly in chemical sensors. We use temporal signals produced by chemical sensors to form vectors to perform the Principal Component…
Multiplication-Avoiding Variant of Power Iteration with Applications
Hongyi Pan, Diaa Badawi, Runxuan Miao +2
Power iteration is a fundamental algorithm in data analysis. It extracts the eigenvector corresponding to the largest eigenvalue of a given matrix. Applications include ranking alg…
Robust Principal Component Analysis Using a Novel Kernel Related with the L1-Norm
Hongyi Pan, Diaa Badawi, Erdem Koyuncu +1
We consider a family of vector dot products that can be implemented using sign changes and addition operations only. The dot products are energy-efficient as they avoid the multipl…
Fast Walsh-Hadamard Transform and Smooth-Thresholding Based Binary Layers in Deep Neural Networks
Hongyi Pan, Diaa Dabawi, Ahmet Enis Cetin
In this paper, we propose a novel layer based on fast Walsh-Hadamard transform (WHT) and smooth-thresholding to replace convolution layers in deep neural networks. In t…
MF-Net: Compute-In-Memory SRAM for Multibit Precision Inference using Memory-immersed Data Conversion and Multiplication-free Operators
Shamma Nasrin, Diaa Badawi, Ahmet Enis Cetin +2
We propose a co-design approach for compute-in-memory inference for deep neural networks (DNN). We use multiplication-free function approximators based on ell_1 norm along with a c…
Discrete Cosine Transform Based Causal Convolutional Neural Network for Drift Compensation in Chemical Sensors
Diaa Badawi, Agamyrat Agambayev, Sule Ozev +1
Sensor drift is a major problem in chemical sensors that requires addressing for reliable and accurate detection of chemical analytes. In this paper, we develop a causal convolutio…
Detecting Gas Vapor Leaks Using Uncalibrated Sensors
Diaa Badawi, Tuba Ayhan, Sule Ozev +3
Chemical and infra-red sensors generate distinct responses under similar conditions because of sensor drift, noise or resolution errors. In this work, we use different time-series…