Vol 1, Issue 1 | May 2026

In accordance with the energy of the no-stationary mixed signal the weights of the hybrid model between Gaussian and Gaussian will be allocated. On the other hand, in many practical areas of biomedical and engineering, ICA is a newest idea in the statistics and extensively utilized approach for the purposes of BSS. EEG and ECG are multi-channel recordings which represent bodily activities. These multi-channel recording are particularly difficult to understand because of the complicated propagation feature of human tissue. The various methods of the ICA, however, extract signals that may be easily associated with specific bodily function. It was based on a non-Gaussanity technique to discover independent sources, are based on an advanced version of the fast ICA method of Aapo Hyvärinen and Erkki Oja. MATLAB methods have been created based on linear IVA and ICA mathematical models in this thesis. These methods are used to identify the de-mixing matrix for the signal mixture, thereby isolating the words of each source. Laplacian distribution capabilities mean that speech signals in themselves are leptokurtic such that both IVA and ICA could be recognized easily. Subjective and objective quality tests were used to evaluate the increased signals from both IVA and ICA. The average signal-to-noise ratio (SNR) result and mean opinion indicate that the ICA technique is better suited for this task.

In this research work, hard turning of AISI 52100 (chrome steel) having hardness of 57 HRC is considered for analysis of machined surface roughness and tool flank wear using CBN cutting tool insert. This chrome steel bears having high hardness, wear resistance, surface finishing and dimensional precision; it is widely used to manufacture mechanical components, notably in balls and roller bearing. The temperature developed during machining is critical for analysis since it effects wear of the cutting tool and increases the surface roughness of the machined surface. The interface temperature, surface roughness, flank wear and chip morphology generated during machining will depend on the machining parameters chosen for this material. Experiments are designed based on Taguchi's Design of Experiment, for three input parameters each has three levels based on an L9 Orthogonal array. The output responses are analyzed based on Signal-to-Noise ratio and statistical tool like ANOVA and regression. The effect of interface temperature and chip morphology on surface roughness and flank wear is analyzed and the optimum cutting conditions are evaluated for minimizing surface roughness of work piece and tool flank wear to a considerable amount. The experimental results indicated that rise in interface temperature increases the surface roughness and tool flank wear. At optimum condition surface roughness value decreases when shape of chip changes from continuous to discontinues type. Results also shows when flank wear increases, shape of chip changes from continuous spring saw tooth wavy type to continuous spring one side flat one side saw tooth type chip.

Induction motors are the most widely used motors for appliances, industrial control, and automation; hence, they are often called the workhorse of the motion industry. They are robust, reliable, and durable. When power is supplied to an induction motor at the recommended specifications, it runs at its rated speed. However, many applications need variable speed operations. For example, a washing machine may use different speeds for each wash cycle. Historically, mechanical gear systems were used to obtain variable speed. Recently, electronic power and control systems have matured to allow these components to be used for motor control in place of mechanical gears. Here an attempt is made to control the speed of Induction motor using generation of variable voltage variable frequency AC source (VVVF) using microcontroller & electronic devices. These electronics not only control the motor's speed, but can improve the motor's dynamic and steady state characteristics. In addition, electronics can reduce the system's average power consumption of the motor.

In this paper, a modular Simulink model implementation of an induction motor model is described in a step-by-step approach. The model is based on two-axis theory of revolving transformation. With the modular system, each block solves one of the model equations; therefore unlike black box models, all of the machine parameters are accessible for control and verification purposes. After the implementation, examples are given with the model used in different drive applications. The model takes power source and load torque as input and gives speed and electromagnetic torque as output.

Wire EDM machines are used to cut all conductive material of any hardness or toughness or those are difficult or impossible to cut with conventional methods. Wire electrical discharge machining process is a highly complex, time varying & stochastic process. In the present research, experimental investigations have been conducted to establish relationship of Material Removal Rate, surface finish and kerf width with current, pulse-ON and pulse-OFF time. Molybdenum wires of diameters 0.18 mm were used. Material tested is P20 steel material. Today, the most effective machining strategy is determined by identifying the different factors affecting the WEDM process and seeking the different ways of obtaining the optimal machining condition and performance. Result of confirmation experiments shows that the MRR increases with current and pulse on-time but machined surface becomes rougher and MRR decreases with increase in pulse-OFF time. The study demonstrates that the WEDM process parameters can be adjusted to achieve better metal removal rate, surface finish and cutting width simultaneously.