The article introduces a new method called "normal product" prior for finding sparse solutions in data. This method uses a distribution that focuses on values close to zero, making it good for finding sparse patterns. The researchers created a two-stage model using this method and used a technique called variational Bayesian to analyze the data. Their simulations showed that this new method is more effective than other similar techniques in finding sparse signals.