In recent years, advancements in wireless technologies and devices have revolutionized our understanding of the capability of wireless networks. from IoT devices to smartwatches use wireless technology such as Bluetooth to connect and communicate with other devices.
These wireless technologies use radio waves to transfer information. With radio waves, intended distances can be short, such as a few meters for Bluetooth or as far as millions of kilometres for deep-space radio communications.
In this article, we’ll be discussing Bluetooth low energy (BLE or Bluetooth Smart) which is a lightweight subset of classic Bluetooth. Bluetooth Low Energy was introduced as part…
Eigenvectors and eigenvalues have many important applications in different branches of computer science. The well-known examples are geometric transformations of 2D and 3D objects used in modelling software or Eigenfaces for face recognition, PCA (Principal Component Analysis) for dimensionality reduction in computer vision and machine learning in general.
In this article, let's discuss what are eigenvectors and eigenvalues and how they are used in the Principal component analysis.
Let's think of a matrix A
Convolutional neural networks (CNN, ConvNet) is a class of deep, feed-forward artificial neural networks that are applied for analyzing visual imagery. Images are high-dimensional vectors and would take a huge amount of parameters to characterize the neural network.
To address this problem, convolutional neural networks were proposed to reduce the number of parameters and adapt the network architecture specifically to vision tasks.
Convolution in terms of mathematics it is an operation on two functions (f and g) to produce a Third Function that expresses the amount of overlap of one function ‘f’ as it shifts over another function ‘g’, therefore…